{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a7b23dec-b8d3-438f-84d7-3beb08e782cd",
   "metadata": {},
   "source": [
    "# Tutorial: Brd4 bindings for Male/Female mouse bulk calling cards data. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23957f8d-186a-4d95-a223-dc67ddeba63b",
   "metadata": {},
   "source": [
    " We will analyze bulk calling cards datasets from [Kfoury et al., PNAS. (2021)](https://www.pnas.org/doi/10.1073/pnas.2017148118), which can be downloaded from [GEO](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE156821). These experiments were designed to study differences in Brd4 binding between male and female cells in a genetically engineered cellular model of glioblastoma (GBM). These nearly-isogenic cells were derived from murine neocortical postnatal day 1 (p1) astrocytes (male and female GBM astrocytes) and were engineered to contain a combined loss of neurofibromin (NF1) and p53 function. These cells were previously shown to display sex differences in important GBM  phenotypes in vivo, including proliferation, clonogenic stem-like frequency, in vivo tumorigenesis, cell cycle regulation, gene expression, and chemotherapy response, that mimic those observed in GBM patients. For more details see [Kfoury et al., PNAS. (2021)].\n",
    "\n",
    " In this tutorial, we will call peaks, annotate these peaks, perform differential peak analysis, and pair differentially bound genomic regions with nearby genes that are also differentially expressed between the sexes. There are 668525 insertions in female qbed data and 613728 insertions in male qbed data. For bulk RNA-seq data, there are 6 samples in total: 3 female samples and 3 male samples. It creates a group by peak anndata for calling cards data. If you want to create a replicate by peak anndata only, please check [Github](https://github.com/The-Mitra-Lab/pycallingcards_data/blob/main/Brd4_bulk-replicate.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9c51fe44-bebe-4dde-8007-5cd516f40f51",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pycallingcards as cc\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scanpy as sc\n",
    "from matplotlib import pyplot as plt\n",
    "plt.rcParams['figure.dpi'] = 150"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "669744b0-c0b2-4e07-a421-b128fc03f2b2",
   "metadata": {},
   "source": [
    "We start by reading qbed data. In these data, each row provides information about one Brd4-directed insertion organized into columns to indicate the chromosome, start point, end point, number of reads supporting the insertion, and the orientation and barcode for each insertion. For example, in the file displayed below, the first row tells us that the first insertion occured into a TTAA on Chromosome 1, whose coordinates start location 3478112 and end at 3478115. There was 1 read supporting this insertion and the transposon is orientated so that the plus strand of the transposon is on the plus strand of the genome. The transposon barcode is TTTGTCCAA. We add another column indecating its respected group. \n",
    "\n",
    "Use ```cc.rd.read_qbed(filename)``` to load your own qbed data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e1c61320-1c1b-4919-8bc8-e7fd730bb6fa",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Chr</th>\n",
       "      <th>Start</th>\n",
       "      <th>End</th>\n",
       "      <th>Reads</th>\n",
       "      <th>Direction</th>\n",
       "      <th>Barcodes</th>\n",
       "      <th>group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3478111</td>\n",
       "      <td>3478115</td>\n",
       "      <td>1</td>\n",
       "      <td>+</td>\n",
       "      <td>TTTGTCCAA</td>\n",
       "      <td>Female_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3481743</td>\n",
       "      <td>3481747</td>\n",
       "      <td>1</td>\n",
       "      <td>+</td>\n",
       "      <td>TATGTACAA</td>\n",
       "      <td>Female_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3481957</td>\n",
       "      <td>3481961</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>TATGTACAA</td>\n",
       "      <td>Female_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3493161</td>\n",
       "      <td>3493165</td>\n",
       "      <td>16</td>\n",
       "      <td>+</td>\n",
       "      <td>TATGTACAA</td>\n",
       "      <td>Female_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3493702</td>\n",
       "      <td>3493706</td>\n",
       "      <td>1</td>\n",
       "      <td>+</td>\n",
       "      <td>CGTTACACA</td>\n",
       "      <td>Female_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1290214</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90802841</td>\n",
       "      <td>90802845</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>CGTTACACA</td>\n",
       "      <td>Female_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1290215</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90803579</td>\n",
       "      <td>90803583</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>TATGTACAA</td>\n",
       "      <td>Female_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1290216</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90803579</td>\n",
       "      <td>90803583</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>TGTCGTGCA</td>\n",
       "      <td>Female_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1290217</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90804429</td>\n",
       "      <td>90804433</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>TATACTCTA</td>\n",
       "      <td>Female_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1290218</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90805130</td>\n",
       "      <td>90805134</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>GACGGCTCC</td>\n",
       "      <td>Female_Brd4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1290219 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Chr     Start       End  Reads Direction   Barcodes        group\n",
       "0        chr1   3478111   3478115      1         +  TTTGTCCAA  Female_Brd4\n",
       "1        chr1   3481743   3481747      1         +  TATGTACAA  Female_Brd4\n",
       "2        chr1   3481957   3481961      1         -  TATGTACAA  Female_Brd4\n",
       "3        chr1   3493161   3493165     16         +  TATGTACAA  Female_Brd4\n",
       "4        chr1   3493702   3493706      1         +  CGTTACACA  Female_Brd4\n",
       "...       ...       ...       ...    ...       ...        ...          ...\n",
       "1290214  chrY  90802841  90802845      1         -  CGTTACACA  Female_Brd4\n",
       "1290215  chrY  90803579  90803583      1         -  TATGTACAA  Female_Brd4\n",
       "1290216  chrY  90803579  90803583      1         -  TGTCGTGCA  Female_Brd4\n",
       "1290217  chrY  90804429  90804433      1         -  TATACTCTA  Female_Brd4\n",
       "1290218  chrY  90805130  90805134      1         -  GACGGCTCC  Female_Brd4\n",
       "\n",
       "[1290219 rows x 7 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Female_Brd4 = cc.datasets.mouse_brd4_data(data = \"Female_Brd4\")\n",
    "Female_Brd4['group'] = \"Female_Brd4\"\n",
    "Female_Brd4\n",
    "#load female CC data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "347f9c6a-8ae1-4480-99d9-4f36b00d7fae",
   "metadata": {},
   "outputs": [
    {
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       "      <th>Chr</th>\n",
       "      <th>Start</th>\n",
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       "      <td>chr1</td>\n",
       "      <td>3493161</td>\n",
       "      <td>3493165</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>GAGGTACAG</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3493275</td>\n",
       "      <td>3493279</td>\n",
       "      <td>1</td>\n",
       "      <td>+</td>\n",
       "      <td>TACTTTCCG</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3493341</td>\n",
       "      <td>3493345</td>\n",
       "      <td>2</td>\n",
       "      <td>+</td>\n",
       "      <td>AGCACAGTG</td>\n",
       "      <td>Male_Brd4</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3493341</td>\n",
       "      <td>3493345</td>\n",
       "      <td>10</td>\n",
       "      <td>+</td>\n",
       "      <td>TGTCCATTG</td>\n",
       "      <td>Male_Brd4</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3493341</td>\n",
       "      <td>3493345</td>\n",
       "      <td>8</td>\n",
       "      <td>+</td>\n",
       "      <td>ATGAAAGCA</td>\n",
       "      <td>Male_Brd4</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>1185697</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90803733</td>\n",
       "      <td>90803737</td>\n",
       "      <td>13</td>\n",
       "      <td>-</td>\n",
       "      <td>TACTTTCCG</td>\n",
       "      <td>Male_Brd4</td>\n",
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       "    <tr>\n",
       "      <th>1185698</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90803733</td>\n",
       "      <td>90803737</td>\n",
       "      <td>9</td>\n",
       "      <td>-</td>\n",
       "      <td>CACGGCGGA</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1185699</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90803733</td>\n",
       "      <td>90803737</td>\n",
       "      <td>17</td>\n",
       "      <td>-</td>\n",
       "      <td>GATCTTATG</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1185700</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90803774</td>\n",
       "      <td>90803778</td>\n",
       "      <td>4</td>\n",
       "      <td>-</td>\n",
       "      <td>ATGAAAGCA</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1185701</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90806562</td>\n",
       "      <td>90806566</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>AGCACAGTG</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1185702 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Chr     Start       End  Reads Direction   Barcodes      group\n",
       "0        chr1   3493161   3493165      1         -  GAGGTACAG  Male_Brd4\n",
       "1        chr1   3493275   3493279      1         +  TACTTTCCG  Male_Brd4\n",
       "2        chr1   3493341   3493345      2         +  AGCACAGTG  Male_Brd4\n",
       "3        chr1   3493341   3493345     10         +  TGTCCATTG  Male_Brd4\n",
       "4        chr1   3493341   3493345      8         +  ATGAAAGCA  Male_Brd4\n",
       "...       ...       ...       ...    ...       ...        ...        ...\n",
       "1185697  chrY  90803733  90803737     13         -  TACTTTCCG  Male_Brd4\n",
       "1185698  chrY  90803733  90803737      9         -  CACGGCGGA  Male_Brd4\n",
       "1185699  chrY  90803733  90803737     17         -  GATCTTATG  Male_Brd4\n",
       "1185700  chrY  90803774  90803778      4         -  ATGAAAGCA  Male_Brd4\n",
       "1185701  chrY  90806562  90806566      1         -  AGCACAGTG  Male_Brd4\n",
       "\n",
       "[1185702 rows x 7 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Male_Brd4 = cc.datasets.mouse_brd4_data(data = \"Male_Brd4\")\n",
    "Male_Brd4['group'] = \"Male_Brd4\"\n",
    "Male_Brd4\n",
    "#load male CC data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4af5a134-d8f1-46fb-8903-d80cec3a3d9b",
   "metadata": {},
   "source": [
    "Since we are interested in differential peak calling, we now combine the two datasets to call peaks on the joint dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "937d6e35-a00f-4815-bbab-62573de83659",
   "metadata": {},
   "outputs": [
    {
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       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
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       "      <td>-</td>\n",
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       "      <td>Female_Brd4</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
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       "      <td>+</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3493161</td>\n",
       "      <td>3493165</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>GAGGTACAG</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2475916</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90803733</td>\n",
       "      <td>90803737</td>\n",
       "      <td>17</td>\n",
       "      <td>-</td>\n",
       "      <td>GATCTTATG</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2475917</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90803774</td>\n",
       "      <td>90803778</td>\n",
       "      <td>4</td>\n",
       "      <td>-</td>\n",
       "      <td>ATGAAAGCA</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2475918</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90804429</td>\n",
       "      <td>90804433</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>TATACTCTA</td>\n",
       "      <td>Female_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2475919</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90805130</td>\n",
       "      <td>90805134</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>GACGGCTCC</td>\n",
       "      <td>Female_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2475920</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90806562</td>\n",
       "      <td>90806566</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>AGCACAGTG</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2475921 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Chr     Start       End  Reads Direction   Barcodes        group\n",
       "0        chr1   3478111   3478115      1         +  TTTGTCCAA  Female_Brd4\n",
       "1        chr1   3481743   3481747      1         +  TATGTACAA  Female_Brd4\n",
       "2        chr1   3481957   3481961      1         -  TATGTACAA  Female_Brd4\n",
       "3        chr1   3493161   3493165     16         +  TATGTACAA  Female_Brd4\n",
       "4        chr1   3493161   3493165      1         -  GAGGTACAG    Male_Brd4\n",
       "...       ...       ...       ...    ...       ...        ...          ...\n",
       "2475916  chrY  90803733  90803737     17         -  GATCTTATG    Male_Brd4\n",
       "2475917  chrY  90803774  90803778      4         -  ATGAAAGCA    Male_Brd4\n",
       "2475918  chrY  90804429  90804433      1         -  TATACTCTA  Female_Brd4\n",
       "2475919  chrY  90805130  90805134      1         -  GACGGCTCC  Female_Brd4\n",
       "2475920  chrY  90806562  90806566      1         -  AGCACAGTG    Male_Brd4\n",
       "\n",
       "[2475921 rows x 7 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Brd4 = cc.rd.combine_qbed([Female_Brd4, Male_Brd4])\n",
    "Brd4"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "972b5eef-6674-4fc7-81a7-389fb8a4d3e5",
   "metadata": {},
   "source": [
    "Optional: filter the insertions with reads greater than 2. Because we use strict quality control on read insertions, even insertions supported by 1 read are likely to be bona fide."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "685aa326-7cc2-4224-93f5-255b14a339e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Chr</th>\n",
       "      <th>Start</th>\n",
       "      <th>End</th>\n",
       "      <th>Reads</th>\n",
       "      <th>Direction</th>\n",
       "      <th>Barcodes</th>\n",
       "      <th>group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3493161</td>\n",
       "      <td>3493165</td>\n",
       "      <td>16</td>\n",
       "      <td>+</td>\n",
       "      <td>TATGTACAA</td>\n",
       "      <td>Female_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3493341</td>\n",
       "      <td>3493345</td>\n",
       "      <td>10</td>\n",
       "      <td>+</td>\n",
       "      <td>TGTCCATTG</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3493341</td>\n",
       "      <td>3493345</td>\n",
       "      <td>8</td>\n",
       "      <td>+</td>\n",
       "      <td>ATGAAAGCA</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3493643</td>\n",
       "      <td>3493647</td>\n",
       "      <td>3</td>\n",
       "      <td>+</td>\n",
       "      <td>TCTACTGCC</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3514553</td>\n",
       "      <td>3514557</td>\n",
       "      <td>7</td>\n",
       "      <td>+</td>\n",
       "      <td>TACTTTCCG</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2475905</th>\n",
       "      <td>chrY</td>\n",
       "      <td>42512546</td>\n",
       "      <td>42512550</td>\n",
       "      <td>3</td>\n",
       "      <td>-</td>\n",
       "      <td>ACGCGCTGT</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2475914</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90803733</td>\n",
       "      <td>90803737</td>\n",
       "      <td>13</td>\n",
       "      <td>-</td>\n",
       "      <td>TACTTTCCG</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2475915</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90803733</td>\n",
       "      <td>90803737</td>\n",
       "      <td>9</td>\n",
       "      <td>-</td>\n",
       "      <td>CACGGCGGA</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2475916</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90803733</td>\n",
       "      <td>90803737</td>\n",
       "      <td>17</td>\n",
       "      <td>-</td>\n",
       "      <td>GATCTTATG</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2475917</th>\n",
       "      <td>chrY</td>\n",
       "      <td>90803774</td>\n",
       "      <td>90803778</td>\n",
       "      <td>4</td>\n",
       "      <td>-</td>\n",
       "      <td>ATGAAAGCA</td>\n",
       "      <td>Male_Brd4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1229664 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Chr     Start       End  Reads Direction   Barcodes        group\n",
       "3        chr1   3493161   3493165     16         +  TATGTACAA  Female_Brd4\n",
       "7        chr1   3493341   3493345     10         +  TGTCCATTG    Male_Brd4\n",
       "8        chr1   3493341   3493345      8         +  ATGAAAGCA    Male_Brd4\n",
       "10       chr1   3493643   3493647      3         +  TCTACTGCC    Male_Brd4\n",
       "17       chr1   3514553   3514557      7         +  TACTTTCCG    Male_Brd4\n",
       "...       ...       ...       ...    ...       ...        ...          ...\n",
       "2475905  chrY  42512546  42512550      3         -  ACGCGCTGT    Male_Brd4\n",
       "2475914  chrY  90803733  90803737     13         -  TACTTTCCG    Male_Brd4\n",
       "2475915  chrY  90803733  90803737      9         -  CACGGCGGA    Male_Brd4\n",
       "2475916  chrY  90803733  90803737     17         -  GATCTTATG    Male_Brd4\n",
       "2475917  chrY  90803774  90803778      4         -  ATGAAAGCA    Male_Brd4\n",
       "\n",
       "[1229664 rows x 7 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Brd4 = Brd4[Brd4['Reads'] > 2]\n",
    "Brd4"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36f55359-784c-4584-978e-e9423ec1296c",
   "metadata": {},
   "source": [
    "Because insertions are discrete, we now need to call peaks to deduce potential binding sites. Three different methods (*CCcaller, MACCs, Blockify*) are available along with three different species (*hg38, mm10, sacCer3*). \n",
    "\n",
    "In this setting, we use ***CCcaller*** in *mouse*('mm10') data. *maxbetween* is the most important parameter for *CCcaller*. It controls the maximum distance between two nearby insertions, or in another words, the minimum distance between two peaks. We recommend using a value between 800-1200 to set *maxbetween*.  *pvalue_cutoff* is also an important parameter and a number 0.0001-0.01 is strongly advised. The setting of *pseudocounts* is largely influenced by library size. For the first time of trial, it can be adjusted to $10^{6}-10^{-5} \\times$ the number of insertions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8d13f5ba-1f41-49dc-b5d9-8d3edbe1f71d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For the CCcaller method without background, [expdata, reference, pvalue_cutoff, lam_win_size, pseudocounts, minlen, extend, maxbetween, test_method, min_insertions, record] would be utilized.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 21/21 [00:21<00:00,  1.00s/it]\n"
     ]
    },
    {
     "data": {
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Chr</th>\n",
       "      <th>Start</th>\n",
       "      <th>End</th>\n",
       "      <th>Experiment Insertions</th>\n",
       "      <th>Reference Insertions</th>\n",
       "      <th>Expected Insertions</th>\n",
       "      <th>pvalue</th>\n",
       "      <th>pvalue_adj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>4196775</td>\n",
       "      <td>4198714</td>\n",
       "      <td>16</td>\n",
       "      <td>12</td>\n",
       "      <td>0.142389</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>4785068</td>\n",
       "      <td>4786551</td>\n",
       "      <td>17</td>\n",
       "      <td>15</td>\n",
       "      <td>0.572576</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>4806673</td>\n",
       "      <td>4807730</td>\n",
       "      <td>21</td>\n",
       "      <td>12</td>\n",
       "      <td>0.477937</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>4856928</td>\n",
       "      <td>4862019</td>\n",
       "      <td>104</td>\n",
       "      <td>44</td>\n",
       "      <td>1.490080</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>4912814</td>\n",
       "      <td>4916593</td>\n",
       "      <td>7</td>\n",
       "      <td>22</td>\n",
       "      <td>0.791756</td>\n",
       "      <td>1.900897e-06</td>\n",
       "      <td>1.024407e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24546</th>\n",
       "      <td>chrX</td>\n",
       "      <td>169936677</td>\n",
       "      <td>169937745</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>1.189526</td>\n",
       "      <td>3.479200e-05</td>\n",
       "      <td>1.673495e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24547</th>\n",
       "      <td>chrY</td>\n",
       "      <td>897430</td>\n",
       "      <td>899700</td>\n",
       "      <td>11</td>\n",
       "      <td>24</td>\n",
       "      <td>0.528165</td>\n",
       "      <td>6.046275e-13</td>\n",
       "      <td>5.162843e-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24548</th>\n",
       "      <td>chrY</td>\n",
       "      <td>1009018</td>\n",
       "      <td>1011799</td>\n",
       "      <td>27</td>\n",
       "      <td>25</td>\n",
       "      <td>0.489073</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24549</th>\n",
       "      <td>chrY</td>\n",
       "      <td>1243715</td>\n",
       "      <td>1246316</td>\n",
       "      <td>24</td>\n",
       "      <td>29</td>\n",
       "      <td>0.504932</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24550</th>\n",
       "      <td>chrY</td>\n",
       "      <td>1282482</td>\n",
       "      <td>1287504</td>\n",
       "      <td>19</td>\n",
       "      <td>60</td>\n",
       "      <td>0.945958</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24551 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Chr      Start        End  Experiment Insertions  \\\n",
       "0      chr1    4196775    4198714                     16   \n",
       "1      chr1    4785068    4786551                     17   \n",
       "2      chr1    4806673    4807730                     21   \n",
       "3      chr1    4856928    4862019                    104   \n",
       "4      chr1    4912814    4916593                      7   \n",
       "...     ...        ...        ...                    ...   \n",
       "24546  chrX  169936677  169937745                      7   \n",
       "24547  chrY     897430     899700                     11   \n",
       "24548  chrY    1009018    1011799                     27   \n",
       "24549  chrY    1243715    1246316                     24   \n",
       "24550  chrY    1282482    1287504                     19   \n",
       "\n",
       "       Reference Insertions  Expected Insertions        pvalue    pvalue_adj  \n",
       "0                        12             0.142389  0.000000e+00  0.000000e+00  \n",
       "1                        15             0.572576  0.000000e+00  0.000000e+00  \n",
       "2                        12             0.477937  0.000000e+00  0.000000e+00  \n",
       "3                        44             1.490080  0.000000e+00  0.000000e+00  \n",
       "4                        22             0.791756  1.900897e-06  1.024407e-04  \n",
       "...                     ...                  ...           ...           ...  \n",
       "24546                     8             1.189526  3.479200e-05  1.673495e-03  \n",
       "24547                    24             0.528165  6.046275e-13  5.162843e-11  \n",
       "24548                    25             0.489073  0.000000e+00  0.000000e+00  \n",
       "24549                    29             0.504932  0.000000e+00  0.000000e+00  \n",
       "24550                    60             0.945958  0.000000e+00  0.000000e+00  \n",
       "\n",
       "[24551 rows x 8 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "peak_data = cc.pp.call_peaks(Brd4, method = \"CCcaller\", reference = \"mm10\", pvalue_cutoff = 0.01, \n",
    "                             maxbetween = 1100, lam_win_size = 1000000, pseudocounts = 0.1, \n",
    "                             record = True, save = \"peak.bed\")\n",
    "peak_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b6b4e1c-aa69-4138-89ac-3d38c8d47fa8",
   "metadata": {},
   "source": [
    "\n",
    "In order to tune parameters for peak calling, we advise looking at the data and evaluating the validity of the called peaks. The default settings are what we recommend, but for some TFs adjacent peaks may be merged that should not be, or, alternatively, peaks that should be joined may be called separately. \n",
    "\n",
    "Below, we plot the combined calling card data in males and females for a region in chromosome 1. The top track displays insertion locations and their read counts. Each dot is an insertion and the height is log(reads+1). The middle track plots the insertion density. The thrid track represents the reference genes and peaks. Finally, the last track represents peak calls.  Below you can see that regions with high densities of insertions are accurately called as Brd4 binding sites."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "09a124e5-a6b8-4f1c-ad8c-f65fc80eb192",
   "metadata": {},
   "outputs": [
    {
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lmTZtWhobGztcr66uLgceeGA+/elP58gjjyw7icm64l+6dGm+//3v5/vf/34ef/zxDtvZZZddMmXKlPzbv/1b6urKf/S+sbEx1157ba677rrMmDEjq1atWmedjTbaKO94xzty0EEH5SMf+Uh23XXXsrcPtCVVDQD0VX/rfACi43qPVjYOAIqzYF7l2ho7zixRAABA9Rk6vNDf6aq1+0x/76ZxtHLi7aw/t+2OyVbbltbeVtsWEmlANar0ZwwAAKpVud9Dzp9b2TgAAACqxIgRI/Kzn/0s/fv3b1V+77335swzzyy5vb///e855phj2iRn+NCHPtRpIo11ufbaa7Pbbrvl4osv7jSRRUtLS37zm9/kAx/4QA477LD885//LHubqz3++ON5//vfn3e+85353//93063nyTNzc2577778oUvfCG77LJLbrrppi7HsKbFixfnYx/7WPbff//8/Oc/bzeRRm+44YYbsssuu+T888/vMJFGkixfvvz1v+cvfvGLdte57777sttuu+WLX/xih4k0kmTFihW5/fbbs8cee+Tiiy/u6kvI4sWLc/LJJ2ennXbKt771rXUm0kiS+fPn5/zzz89OO+2Uc889t6gHxUtx0003ZZdddsk3v/nNDhNpJIV9f/bs2Tn66KNz4IEHZtGiRRWNo1q1tLTkrLPOypgxY3LVVVd1mEgjKSQFuP3227P33ntnypQpZf2tV65cmTPPPDO77bZbvvWtb5WUpOHvf/97fvrTn2by5Ml5y1veUvK2k+RnP/tZdtpppxx33HH59a9/3WkijSR55ZVXcsMNN2T//ffPhz70ofz9738va7sduf/++/PWt741J554YoeJNNZX8+bNyz777JPDDjssN998c6eJNJLCvnH33Xdn0qRJGTNmTGbNmlXxmGbOnJm3vvWtOe200zpNpJEUEsyccMIJ2WOPPcr+u0+fPj1vectb8pnPfCa//e1vi/7MLFmyJPfcc0++9rWvZbfddsvdd99d1vaB9kmmAQB91fKllavXsCi59frkwtOTc08u/L5taqEcgMoo97i9tpGjk0knVKYtAACAvqRhUeHh+UFDym+jvT7TyhXltfXa4uSzhyVf+GhhvOyZJ9uuM/H4ZKciZ3toL7a1x+U2GZbU9W+3ehuDhiSnX1TcurC+mnh84bNTDGMmAABsqCp5/wgAXedePACoCvvuu2/OO++8NuXnnXdebrvttqLbWbFiRY466qgsXLiwVfmb3vSm/OhHPyo7vgsuuCCTJ0/Oq6++WlK92267Lfvss0+efLKd7z6L9POf/zxve9vbcscdd5RV/8knn8wRRxyRb3/722XHsKaXX345Y8eOzfXXX1+R9irle9/7Xo4++uiSEji89tpr+ehHP5pbbrmlVflNN92UAw88sKQkAytXrswpp5ySSy+9tOg6a3v44Yez55575pJLLsmKFaV/77548eKcccYZ+ehHP1qxBCcXXXRRjjjiiJKTwvz2t7/NAQcckFdeeaUicVSrlStX5qijjso3vvGNkv7mLS0tufTSS/PJT36ypO01NjbmiCOOyDnnnLPOxArrsq4kGGtramrKcccdl6OPPjrPPPNMWdv85S9/mX322adiSS9uvfXWHHjggUUlrVnf/PSnP8073/nO/P73vy+r/iOPPJIDDzww//Vf/1WxmG644YYcfPDBJZ8T//znP2fs2LElHZOTQhKsQw89dJ1JO4pR6v4OdK6utwMAANrR1JgsLDMj7MDBrduZelkya3rSvNaF9COzk5uvK8zkN+mEpH99+fEC0Pr4W47aOsdkAACgOq0eo5p5V7Kqubw2Ousz1fVPGpeX127zymTpksJY2TdOSLbatpDAYvBG/4r7yQWlx9bZuFwxBg1Ozr6iEAdUs/oByclnd/55MWYCAMCGrtzvIbv6/SUArbkXDwCqzimnnJIZM2bkF7/4xetlLS0tmTx5cmbPnp3tt99+nW2cdtppbR4cHjBgQG644YZsuummZcX1i1/8Il/+8pdbldXV1eWd73xntttuuwwaNCjPPfdcHnzwwXYTDjzxxBM55JBD8vvf/z7Dhw8vadtXXXVVPv3pT2fVqlXtLt9hhx0yZsyYDB8+PP369cs//vGP/P73v89LL73Uar2WlpZ89atfzdKlS/Of//mfJcWwpubm5nzoQx/KvHnzWpVvueWW2WuvvbL55psnSZ599tk8/PDDWbq0ZxJL/vKXv8yUKVPS0tLyetnw4cPzzne+M1tuuWVaWlry9NNPZ9asWW0SCKxatSqf+MQn8te//jVbb711Zs2alaOOOqpVYoMhQ4Zkn332ydZbb50BAwbk2WefzcyZM7NkyZI2sfz7v/973vve92a33XYr6TXMmTMn733ve9skgllts802y1577ZUtttgigwYNyksvvZR58+a1mwTgF7/4RSZMmJDp06entra2pDjWdPXVV+fUU09tVbbxxhtn7733zlZbbZVBgwblxRdfzH333dfuvv/nP/85J598cq666qqyY6h2n/nMZ3LjjTe2Ktt6661f/zytWrUqzzzzTH73u9+1myDluuuuy8EHH5xjjz22qO199atfbZM8ZrWNNtooo0ePzg477JCNNircG9HQ0JCXX345jzzySJ5//vnSXtwampqa8sEPfjDTpk1rd3n//v2zxx57ZPvtt8+wYcOyePHi/P3vf88DDzzQJsnI888/n3e/+92ZMWNGdt9997Jjeuihh/Kxj32s1TGhpqYmu+++e3bcccdsttlmWbRoUZ599tnMnj277O30hhtvvDEf+9jHOjx37Lzzztltt92yxRZb5OWXX85jjz2WuXPntllv5cqVOemkk9LS0pKTTjqpSzHdfffd+fjHP97q7zlw4MDsvffeeeMb35iNNtooL7/8ch544IF2k60888wz+dSnPpVf/epXqampWef25syZk+OOOy7NzW3vi6qpqcmuu+6anXfeOcOHD8+AAQOyZMmSvPrqq3n00Ufz6KOPSp4B3aymZc2rNgCg9zU1JhefmSyYt+512/PhY5MJE0trZ+Towg3L9QPK2yYAhVlHbrq6vLq77Zl8+t+TocMqGxMAAEBvK2esa9iIZMttkqblhQd/Ro1J9hvfcZ/pu19N/lKZWUCSJIOGJGf9ILnyvOLi3nGX5LTz/jW21tXxvdV22i354reM2bHhaFiUzJyWzJ9bmEG7mM8/AABsCMr9HnL1/SMAdJ178QCg4g488MD89re/bVX2yU9+sscfgm9oaMhee+3VZhb5vffeOzNmzEh9fcdJsn7+85/nox/9aJvy//7v/86JJ55Y1PbXfkB3+PDhqa2tfT1RwIABA3LmmWfmhBNOyGabbdZq3ZUrV2batGk55ZRT8uijj7Zp++Mf/3iuu+66ouJIkgceeCD77bdfmwfJhwwZkuOPPz6f//zns8MOO7Spt2rVqvzqV7/K6aefnj/+8Y+tlvXr1y933XVXDj744HVu/6qrrspxxx3XqmyrrbbKCy+88Pr/3/ve9+Y///M/s88++7R571paWjJjxowccMABbdreYYcd8re//a3N+sVYezvDhg1Lv3798vLLLydJxowZk29961sZP358m0QSDQ0N+Y//+I9ccsklbdr99Kc/nQsuuCBvectbXk8a8KY3vSnnnHNOjjjiiAwY0Pp6srGxMRdeeGG+9rWvtXlY+5BDDukwaUB7Fi1alD333DNPPfVUm2VHHXVUTj311Oy9997tPkD+yCOP5KyzzsrPfvazNsu+9rWvFZU85amnnsqb3vSmVmXbbbdd/vnPf76ewGH06NH55je/mfe///3p379/q3VXrVqVn//855kyZUq7CRdmzZqVd73rXe1ue8WKFWloaHj9/yeddFKmTp3aap2bbropY8eOXefrGDp0aJvYKqm99/9HP/pRUYks2vs8jRo1KvPnz3/9/x/4wAfy9a9/PW9/+9vb1F+2bFkuuuiifOMb32hzTBg2bFieeeaZDB7ceSLXRx99NLvuumub/XWvvfbKWWedlUMOOaTT9++ll17KXXfdlVtvvTU33XRTNtlkk1bHg85MmTIll156aZvyXXbZJV/+8pdz1FFHtRv/4sWL8/3vfz/f+ta38sorr7Sp++CDD67zdSftn+PWPJ4NHDgwp5xySr7whS9kq622ajeORx99NHvuuWcWLVr0+ns4a9asfOhDH2q17sSJE/O9731vnTENHDjw9aQla1t7X9t+++3bPT6056mnnsruu++eV199tc2yww47LGeffXa7SUgeffTRnH322bnmmmvaLOvfv3/uu+++7LXXXkXF0N5xuq6u7vVz6Q477JCzzjorRx55ZAYNGtSm/t13353Pfe5zWbCg7WQ7P/nJTzJp0qR1xnDAAQdkxowZrco23njjfO1rX8txxx2XESNGdFi3qakpDzzwQG655ZbceOONeeKJJ3LHHXfkfe973zq3CxRHMg0A6GuuuSS5947y6tbWJedfW7ixuNR2Djg0mTylvO0CkDQsTL74sdLr1dYm51/noRAAAKA6lTvWVcpY1dNPJGcVdzNa0QYNSZa9Vvz6a8bblfG9ztoFAABgw9SwMPnS5KS5hNkJ17x/BICucy8eAFRcew8aF/tAcDE23njjNskIOjJnzpy8613vyvLly1uVf/7zn+8wnsceeyx77bVXm4eHJ06cmOuvv77oODub7X7EiBH59a9/ndGjR3faxrJlyzJx4sTcfPPNbZbdeuutmTBhwjrjeOWVV7LHHnu0eXh69OjRueGGGzJq1Kh1trFy5cp87nOfy+WXX96qfOutt87jjz/e7gPMa2rv4f81XXDBBTnttNPWGUd7KplMY00f//jH86Mf/WidCRW+8Y1v5KyzzmpVNnDgwBx22GG58cYbkyTjxo3L//3f/3X4sPtqV199dZtkCjU1NXn88cfbJKjoyIc//OHcdNNNrcqGDRuWa6+9tqj9JUl++MMf5rOf/WxWrvzXeEW/fv3yhz/8IXvuuWenddtLprGmT3/607nssstSV1fXaTuPP/54xo4dm3/84x+tyidPnpyrry4uMemxxx7bZt177rknBx54YFH1u1Olk2msVldXl//5n//JZz7zmXW2c/PNN+dDH/pQm8/LD3/4w04/r0nyzW9+M1//+tdblY0fPz4333xzp4mK2rNw4cLccMMN+exnP7vOdW+66aZ8+MMfblP++c9/Pt/5zneKOjc89thjmTBhQpvkCieffHIuuuiiddZv7xy32tZbb5277rorb33rW9fZztp+85vf5D3veU+rskokoio3mUZLS0sOOOCAzJw5s82yiy++OFOmrLtfPHXq1HziE59ok3Rl1KhRmTNnzjrPHUnnx+kJEybkpz/9aYYMGdJpGy+99FL233///PWvf21VfsABB3T4t1zt6aefzvbbb9/qc7Lxxhvnd7/7Xcl/51WrVuXWW2/NzjvvnF133bWkukDH+vV2AADAGhoWJrOml19/7LjCjRDltDNremHmPwDK18lATIfecaCb2AAAgOrUlbGuUsaqNtm0vG10ppREGsm/4u3q+N7aZt5lzA4AAGBDN3R44X6QUqy+fwSArnMvHgD0mKlTp2bzzTevyE8pCS322GOPXHrppW3K/+u//is33HBDm/Lly5fnyCOPbJNIY9SoUbniiitKf+HtqK+vzx133LHORBpJMmjQoPz0pz/NPvvs02bZmWeeWdT2zjnnnDYPTo8cOTK//vWvi0qkkRQe0L/sssvywQ9+sFX5888/X3Rig46ceeaZZSfS6C7vfe97c+21164zkUZSiH/kyJGtypYvX/56Io0xY8bklltuWWcijaTw4PzBBx/cqqylpSU/+clPior7tttua5NIY/Dgwbn99tuLTqSRJJ/61Kdy3nnntSpbtWpVzj///KLbaM+RRx6ZK6+8cp2JNJJkp512yoUXXtim/MYbb0xTU1OX4qhml1xySVGJNJLkgx/8YP7t3/6tTfmPf/zjddZtL8HCpZdeWnIijSQZPnx4UYk0mpqa8vnPf75N+SmnnJLvfe97RSdZevOb35w77rgjm266aavyyy+/PAsXLiyqjfYMGDAg06dPLyuRRl90xx13tPt3Puuss4pKpJEUklB9//vfb1M+f/78XHvttV2Kb999981NN920zkQaSSGB1f/+7/+2Kb/33nvzzDPPdFp35syZbRLOnHTSSWX9nfv165cPfvCDEmlAhUmmAQB9yYxppc0ksqaRo5NJJ5TfTvPKZOa08rYNQOHYW2SW6la22LrysQAAAPQFXRnrKmWsakYfGNNaHW9XXnN7VjUbswMAACCZeHzhvpBirHn/CABd5148ANggfOYzn8kxxxzTpvzTn/50FixY0KrsC1/4Qh566KFWZYMGDcoNN9xQVDKEYpx66ql5+9vfXvT6AwcOzOWXX57a2tpW5Q899FDuv//+Tuu++uqrufzyy1uV9evXL9dff31GjBhRfNBJampqcuWVV2bw4MGtyi+66KI2DxoXa7fddsvXv/71sup2l4EDB+bqq69OTZGT8NXV1eVTn/pUh8uvvvrqoh/yT5L/9//+X5uy3//+90XVveCCC9qUnXPOOe0mY1mXU089Ne94xztald144435+9//XnJbSeFh9iuvvLKkOkcffXS23rr1vdhLly7Nn//857JiqHbjxo3LiSeeWFKdU045pU3ZH/7wh3V+pp977rlW/x8xYkSbpDKV9pOf/CTPPvtsq7I99tgj3/nOd0pua8cdd8w555zTqmzp0qW57LLLyo7va1/7Wt7ylreUXb+vaS8R1e67754zzjijpHY+85nP5L3vfW9R7Rerf//++clPflJUYp7V3vWud2XvvfduU/7AAw90Wm/tfX11W0DfIZkGAPQlC+aVV2/TEckp5yT967vWzvy55dUDoPxj72OPVDYOAACAvqLcftJqxY5VdXU7lTJ/bvfEYswOAACA+gHJyWcnBxya1HZwA3htXWH5mvePANB17sUDgA3GZZdd1uYh58WLF+fII4/MsmXLkiTXXXddrrjiijZ1//u//zujRxeZBHEdBg8enNNPP73keqNHj87EiRPblK8rOcGVV16ZV199tVXZxIkTs+eee5YcQ5Jsvvnm+eQnP9mqbMGCBfnrX/9aVntf+MIX0r9//7LqdpePfexjecMb3lBSnUMOOaTd8ve+971529veVlJb48aNa1M2Z86cddabPXt2fvvb37Yq23777fP5z3++pO2v6bTTTmv1/+bm5tx2221ltXXiiSdmk002KalObW1tDjvssDblDz74YFkxVLuvfvWrJdfZdddds/POO7cqe/XVV/PYY491Wm/lypWd/r87XHjhhW3KzjvvvPTrV95j1J/61KcybNiwVmW//OUvy2pr0KBB+dznPldW3b7o6aefzl133dWm/JxzzmmT2KkY559/fpuyhx9+OL/73e/Kim/SpEnZYYcdSq53+OGHtylb1/GkvX17xYoVJW8b6D6SaQBAX7J8aXn1ho9ofSNEue2UWw+guzUsSm69Prnw9OTckwu/b5taKO8rHHsBAABa62p/5/FHiuv/9ZV+1fKl3RNLX3l9AAAA1a6vfydZPyCZPCU5/9rkw8cmu+2Z7LhL4feHjy2UT54ikQZApbkfBAA2GIMHD86NN96YjTbaqFX53Llz87nPfS6PPPJIjj/++Db1jj322Bx33HEVi+PDH/5wNt5447LqTp48uU3Z2skT1nb77bcX1U4pxo8f36Zs5syZJbdTW1ubSZMmdSmW7vCRj3yk5Dq77rpruw/0H3HEESW3NWzYsDbJPJ577rm0tLR0Wq+9v/WkSZNSV9dB4s4ijBs3rs3rKudvnSRHHnlkWfV23333NmXPPfdcWW1VsxEjRuTAAw8sq2457/GWW27Z6v+vvPJKu8kXKuWZZ57JvHmtkyG+4Q1vyMEHH1x2mwMHDsy73/3uVmVz5szJ0qWl9/cmTJiQTTfdtOxY+poZM2a0OeZstdVWed/73ldWe3vssUfGjBnTpvzee+8tq72ePJ6sva8nyc9+9rOytg90D8k0AKAvGTi4vHoLX0pWNHW9nXLrAXSXpsbkmkuSLx2T3HR18sjs5Im/Fn7/4qpC+TWXtD4G9hbHXgAAgNa62t9pXF5c/6+v9KsGDu6eWPrK6wMAAKhW69N3kkkydFgyYWJy6rnJ6RcXfk+YWCgHoPLcDwIAPeaTn/xkWlpaKvJz7LHHlhXDLrvskssvv7xN+Y9+9KO8+93vzmuvvdaqfPTo0fmf//mfsrbVkQkTJpRd9+CDD87AgQNblT322GN5+eWX211/xYoVuf/++1uV9e/fPwcddFDZMSTJnnvu2absvvvuK7mdXXfdNZtsskmXYukO++67b8l1Bg4c2G6SlHLaSpLNN9+81f9XrVqVxYsXd1qnvYfS20t8Uophw4Zlhx12aFVWzt966NChectb3lJWDFtvvXWbsoaGhrLaqmbvete7UlNTU1bdct7j9vbtY445Jvfcc09ZMaxLe/t3e8leSrX28WzFihX54x//WHI7++yzT5fi6Gt+97vftSk79NBDU1tbW3abH/rQh4raTjHGjh1bVr1K7evXX399zjzzzDQ19ZExZdjASaYBAH3JyNHl1XvlpeSiMwo3eHSlnVFts/gB9JqmxuTiM5N770iaV7a/TvPKwvI1j4G9pdxj75t3q2wcAAAAfUW5/aT2dNb/q+R2umLUmO6JxZgdAABA91nfvpMEoOe5Fw8ANjiTJk3KCSec0Kb8pZdeavX/jTbaKDfccEMGDRpU0e3vscceZdetra3N6NFtr19mz57d7voPPfRQmwQhO++8c/r37192DEmy2WabtSl77rnnSm5nzJi+d001ZMiQDBtWXkLL9pJpbLPNNhVr69VXX+1w/ZaWlnaTXJSbwGJNa/+9n3/++ZLbeOMb31h2oof2Eq509l5sqMrd15Ly3uNjjjmmTSKLF198MQcddFD222+//OAHP8izzz5bdkxrmzVrVpuy7ti/k+o5nnXFnDlz2pS1l0ipFO3V7+j81ZnBgweXfZwuZ18fNWpUu8lSzjnnnOywww756le/mgceeCCrVq0qKyag6yTTAIC+ZP/xSZkDAFkwL5l62b/aqa0rrX5tXbJf17KKAlTU1MsKx7ZirHkM7C37l3kMfbH0AWMAAID1QjljVOvSXv+v3P5YJa0eW+uO12zMDgAAoPusb99JAtDz3IsHABukiy66KHvttVen61xxxRUZNWpURbfbr1+/jBw5sktt7LLLLm3K/vnPf7a77tNPP92m7JFHHklNTU2XfoYMGdKm3YULF5b8Wtp7iL23bbrppmXXra2trVh77bW1cmUHiUKTLFq0KEuWLGlTvsUWW3T57/2HP/yhVZvLly/P0qVLS3o95T74niR1dW2v1zt7LzZUPf0e77bbbvnc5z7X7rJZs2bl+OOPzzbbbJOdd945xx13XH7wgx/k4YcfLjvG9o5nX/rSl7q8f7f3GqrleNYV7Z1Xdtuta5OMtpf8ZO1EVsXojePJhRdemPr6+jblzz//fL797W/nne98ZzbbbLNMmDAhZ599dn79619n2bJlZccJlEYyDQCoJrOmJw2LkqHDk7HjSqs7dlwytPwOA0BFNSwsHNNKsfoY2Fue+1t59R74Te/GDQAA0F3KGaMqxtr9v3L7Y5W0emytO17z83+vbHsAAAAUrI/fSQLQ89yLBwAbpAEDBuSGG25oNylEkpxwwgmZOHFixbe70UYbpV+/rj3u115yhldeeaXddct5ILxcixaV3p/eZJNNuiGSrmnvQeu+1F5HevJvnZT+9+6p92FD1hvv8YUXXphJkyZ1us5jjz2Wq666Kscff3ze+ta3Zsstt8wnPvGJ3HrrrVmxYkXR23I861ntnVe6kmwoaT8JRmNjY8lJJ3pjX993331z3XXXZdCgQR2u88orr+T222/P1772tRx88MHZdNNN8+53vzuXXnpp/vGPf/RgtLDhkUwDAPqSGdOSlpby6zevTGZOK/x74vHJyNHF1Rs5Opl0QvnbBai0GdMKx7RSrHkM7A3XXFpevVXNvRs3AABAd5p4fLLZlpVtc+3+X7n9sUoZsWXrsbVSxuWKcfUllWsLAACAf1kfv5MEoHe4Fw8ANkizZ8/Oa6+91u6yXXfdtVu2ufHGG3e5jfYe2O4LyTRKeSh+NQkWKqenk2mU8/em+tTV1eUnP/lJrr766my33XZF1XnxxRfz4x//OB/4wAey/fbb59JLL01TU9M66zme9az2zitdTRjSUf1ykpf0hiOPPDJ//OMfc+ihhxa1flNTU+69995MmTIl22yzTT71qU/lqaee6t4gYQMlmQYA9CUL5nW9jflzC7/rByQnn50ccGhS20Gnq7ausPyUc5L+9V3fNkCllHs8XH0M7A0vv1h+3d6MGwAAoDvVD0g237ry7a7Zj+pKf6wSRmzdemytmHG5Urxs9gkAAIBusT5+JwlA73AvHgBscB5//PF86lOf6nD5v//7v+fBBx+s+HaLeWB8XRobG9uUDRgwoN11JTzYcPhb05smT56cRx99ND//+c9zxBFHZNNNNy2q3vPPP58pU6bkXe96V5588slO17WP96z6+rb93q6ewzqq39E5rC/abbfdcvvtt+dPf/pTvvjFL2bnnXcuqt7KlSvzox/9KKNHj85PfvKTbo4SNjzVlc4IANZ3y5dWto36AcnkKcnhkwszo8yfW1g+cHAyakyy3/hk6LCubxOg0so9HlbiOFqullXl1+3NuAEAALpb0/LKt7lmP6or/bFKaO/1tTcu98js8trv7dcHAABQrdbH7yQB6D3uxQOADUZjY2OOPPLIvPrqq+tcZ/bs2UU/FF6MzrZZrIaGhjZlw4a1f50yePDgNmV77bVX7rzzzi7Hsbba2tqKt0nx2vtbJ8kzzzzTLQ+qDx8+vOJtsn6rr6/PEUcckSOOOCKrVq3KQw89lFmzZuV3v/tdZsyYkWeffbbDug8++GDe+9735v7778/mm2/e7jrt7eMXXHBBjj322Eq9hE63taEZNmxYXnvttVZlXT2HtXf+qqmpqeh5tqeMGTMm3/nOd/Kd73wnzz33XGbMmJH77rsvM2bMyJ/+9Kc0Nze3W2/JkiX5xCc+kfr6+nz0ox/t4aihekmmAQB9ycAKdKjaa2PosGTCxMIPwPqg3ONhJY6j5arpl7S0P6ixTotfTRoWuakCAKC7NCxKZtxZmG3Uja3Q87qjr7Zmm13pj1VCXf/k1usLyTL++XzS1JjUD0w23yp5y16FY82Eicn/m5CsKiPOmn6OYwAAAN1hffxOsiv0LQEqw714AFD1vvCFL2TOnDmtyoYMGZL6+vosWrTo9bInn3wyxx13XH7xi19UbNuNjY1ZtGhRh8kvivHCCy+0KevoQeStt966Tdmrr76aESNGlL19+qb2/tZJ4UF1f296Wr9+/bLnnntmzz33zEknnZQkefzxx3Prrbfm+uuvz+9///s2dZ544omcfvrpueKKK9ptc+utt87cuXNblTU1Ndm/u8mwYcPyzDPPtCpr7/xTivbqb7zxxut9MqY3vOENOfroo3P00UcnSRYvXpy77rorN910U2688cYsX956Ep+WlpYcf/zxOeSQQ7LJJpv0RshQdfr1dgAAwBpGju56G6PGdL0NgN5W7vGwN4+Bm21Rft1/Ppd86ZjkmkuSFU2ViwkAYEPX1Fi4xvrSMclNVxcedH/ir4Xfv7jKNRj0lEqMea1tzf5fV/pjlbDgz4VjzIJ5yaKXktcWJ4v+Wfj/msea4e3PjrJONXEcAwAA6A7r43eS5TBGBgAAULQf//jHufzyy9uU/+AHP8jVV1+dmpqaVuU33XRTLrzwworG8NBDD1W8/pvf/OZ21915553blD3//PNpbu7FyQzoFltuuWU23njjNuVPP/10L0QDbe20006ZMmVK7r///sycObPd49ZVV12VV155pd367R3P7N/dZ/vtt29T1tXz1+zZs4vazvpu4403zkc+8pFce+21efrpp3PMMce0Wefll1/ONddc0wvRQXWSTAMA+pL9xyf9upAxr19tYcYQgPXd/uOT2rrS6tTW9e4xcPIXula/eWVy7x3JRWcUbmgDAKBrmhqTi88sXGM1r2x/Hddg0DPK6eN1Zu3+X1f7Y13W0vni1ceaAQPLa7652XEMAACgO6yP30mWyhgZAABA0f7617/ms5/9bJvy//f//l8+/vGP5wMf+EBOO+20Nsu/8pWv5P77769YHF1p67nnnmvz8PhGG22Ut7zlLe2uP3r06Awc2Pp7zCVLluTBBx8sOwb6ppqamrzjHe9oU/7b3/62F6KBzo0dOzZ33313hgwZ0qp85cqVHe6ze++9d5sy+3f32WeffdqUdfVc2F79fffdt0tt9nUjRozINddckw984ANtlv3qV7/qhYigOkmmAQB9ydDhyRZvKL/+Fm9Ihg6rXDwAvWXo8GTsuNLqjB3Xu8fAXfdIBg1Z93rrsmBeMvWyrrcDALChm3pZ4dqqGK7BoHuV08frzNr9v133qFzb3enZp5K1ZqqqGMcxAACA0q2P30mWyhgZAABAUZYuXZqPfvSjee2111qVv+1tb8sll1zy+v/PPffc7Lfffq3WWbFiRY4++ugsXLiwIrFcf/31Fa379re/PbW17U/4WV9fn4MOOqhN+c0331x2DPRd73vf+9qUbeh/67q6tolWV61a1QuRsLbtt9++3QQDf/vb39pd/5BDDkm/fq0fl/7LX/6SRx99tFvi6w19aX9917ve1absV7/6Vf75z3+W1d7y5cvz85//vKjtVKPPfe5zbco62teB0kmmAQB9ScPC5J/Pl1//n88nDYsqFw9Ab5p4fDJydHHrjhydTDqhe+Mpxlk/qMyDUbOmO54DAHRFw8LCNVUpXINB9yqlj9eZ9vp/f5nT9XZ7SktL97XtOAYAAFC69fE7yWIZIwMAACjaiSeemIcffrhV2SabbJIbbrghAwcOfL2srq4uU6dOzeabb95q3b///e855phj0lKB7wPnzZuXmTNnllxv5cqVueKKK9qUH3HEEZ3W+/jHP96m7L/+67/yyiuvlBwDfdvRRx/dJrHKrFmz8pvf/KZ3AuoDNt544zZly5Yt64VIaM8OO+zQpmzp0qXtrrvlllvm4IMPblN+zjnnVDqsXtOX9td99903m222Wauyjs5Dxfjxj3/c5rzTv3//HHLIIeWGuF4pZV8HSieZBgD0JTOmJc0ry6/fvDKZOa1y8QD0pvoByclnJwccmtS2zaKapFB+wKHJKeck/et7Nr72DB+RnHdtMnBw19pxPAcA6Jpy+teuwaB7rdnH69f+rEed6qz/d82llYlxfec4BgAAULr18TvJYhkjAwAAKMr//u//5uqrr25TfuWVV+bNb35zm/I3vvGNue6669KvX+vH8m6//facd955FYnppJNOSnNzc0l1LrnkksyfP79V2eDBgzN58uRO6x155JHZdtttW5U1NDTkc5/7XEnbp+/bbrvt8tGPfrRN+YknnpiGhoZeiKj3bbLJJm3KnnvuuV6IhPY8++yzbcq23nrrDtc/9dRT25Rdd911ueOOOyoaV2/pS/vrwIED82//9m9tyr/1rW+1+3frzCuvvJLTTz+9TfmRRx7Z6d+7mpS6rwOlkUwDAPqSBfO63sb8uV1vA6CvqB+QTJ6SnH9t8uFjk932THbcpfD7w8cWyidP6Vs3rQ0fkfzX/yWnnZdstmX57TieAwCUr9z+tWsw6F6r+3gXXFfo040cnQwbkQzZOBm2eeH/hx5d+Cml//fyiz39SvouxzEAAIDSrY/fSRbDGBkAAMA6zZ07NyeddFKb8s9//vM58sgjO6x3yCGHtPvg75lnnpkZM2Z0Oa6HHnooJ554YtHr//rXv84ZZ5zRpvyTn/xkhg4d2mnd/v3759vf/nab8p/85Cf54he/WHJSj7U9/fTTufbaa7vUBpVz7rnnZsCAAa3K/vKXv+TDH/5wFi1a1KW2lyxZkksuuaRLbfS0nXfeuU3ZnDlzeiGS6vLaa6/l3HPPzcKFC8tu44UXXsgvf/nLNuW77757h3Xe9773Zdy4ca3KmpubM3HixNx7771lx7La3XffnQceeKDL7ZRr2223zcCBA1uV/fnPf86KFSt6JZ4TTzwx/fv3b1W2ZMmSfOQjH8mSJUuKaqOpqSlHH310Xnyx7b0/U6ZMqUic3e2KK67I7Nmzu9TGD37wgzZlne3rQGkk0wCAvmT50r7RBkBfM3RYMmFicuq5yekXF35PmFgo76t22T057+rCjXblcDwHAChfuddSrsGgZ6zu433pgkJijUtuSC64tvD/jxxX+Cml/9eyqsdC7/McxwAAAMq3Pn4n2RljZAAAwHrm6quvTk1NTcV+PvShD3W6vcWLF+fII4/MsmXLWpW//e1vz3e/+911xnvWWWflPe95T6uy1Q9tt/dQcDH69fvXo36XX355Jk+enFdeeaXTOldddVUOP/zwNDY2tirfeuutc+655xa13Y997GM54ogj2pRfeOGFOfjggzN3bmmJF5uamnL77bdn0qRJ2XHHHfO///u/JdWn++y444654IIL2pTfc8892WOPPXLrrbempaWl6PZaWlryhz/8IV/84hezzTbb5OSTT65gtN1vjz32aFN2ww035OWXX+6FaKrHihUrcsYZZ2S77bbLiSeemJkzZ2bVquLv7fjb3/6WCRMm5NVXX21Vvuuuu+Ztb3tbp3WvvPLKDBvWejzv1VdfzUEHHZSvf/3raWhoKDqOJHn++efz/e9/P7vvvnvGjRuXRx55pKT6lVRXV5e3vvWtrcpeffXVXH/99b0Sz3bbbZdvfOMbbcp///vf55BDDsnjjz/eaf1nn302H/jAB3LXXXe1WXbCCSdk7733rlSo3eq2227LXnvtlYMOOijXXXddSfvYihUr8pWvfCU/+9nP2iz72Mc+VskwYYNW19sBAABrGDi4b7QBQOWUe1x2PAcAKJ9rMNiw1PRLWro2G1LVcBwDAABgNWNkAAAAnfrMZz6TBQsWtCrbdNNN87Of/Sz19fXrrN+vX79cf/31edvb3pYXXnjh9fLnnnsun/jEJ3LnnXe2So5RjG233TZvf/vb8/Of/zxJcu2112batGn5xCc+kQkTJmTbbbfNoEGD8vzzz+f+++/PddddlwceeKDdtv7nf/4nm266adHbvuqqq/K3v/0tDz74YKvy3/72t9l9991z0EEH5f3vf3/Gjh2b7bbbLsOGDUttbW0aGhryyiuv5LHHHsuf/vSn/PGPf8xdd92VxYsXl/Ta6TknnXRSHn744fzgBz9oVf63v/0tH/jAB7Lrrrvmox/9aPbbb7+MGjUqw4cPz6BBg7J48eI0NDTk73//e+bOnZs5c+bkrrvuyjPPPNNLr6Trdtttt+y0006tHvp/6aWXsvfee+fkk0/Ovvvum6222ioDBw5sU3fo0KHp379/T4a73nnttdfy/e9/P9///vez9dZbZ/z48dlrr72yxx57ZJtttsmwYcMyZMiQLFu2LM8//3zmzp2bW2+9Nddff32bBEFJcv75569zm9ttt13+7//+L+973/tatdHc3JxvfvObueiiizJx4sS8+93vztvf/vaMGDEim266aZYvX56Ghoa89NJL+fOf/5w//elPmTlzZu6///6SEsx0tw984AP54x//2Krs3/7t3/Lggw/msMMOy0477ZSNNtqozfln4MCB2WijjSoez1e+8pXceeedmTFjRqvy++67L6NHj87kyZNz5JFHZtddd82IESOycOHCPPbYY/n5z3+eH/3oR+0mnthll12KSmrV19xzzz255557Ul9fn4MOOij77LNP9txzz9ePo5tuummam5uzaNGiLFiwIPfcc0+uuuqqPPXUU23a+shHPrLeJBOB9YFkGgDQl4wcnTwyu2ttjBpTmVgAqIxyj+2O5wAA5XMNBhuWzbZI/vl8b0fRNziOAQAAsJoxMgAAgA7993//d37605+2Kf/Rj36UN73pTUW3s+WWW+b666/Pe9/73jQ3/2sCgOnTp+eb3/xm/uM//qPk2K644or8+c9/zvz585MkL774Yi688MJceOGFRbdx1lln5UMf+lBJ2914440zffr0HH744W0eik6SX//61/n1r39dUpv0Xf/zP/+T+vr6fO9732uz7C9/+Uu++c1v9kJUPa+mpiYnnHBCTjvttFblTzzxRL7whS90Wveee+7JgQce2I3RVZfnn38+V111Va666qqy6p922mk57LDDilr3wAMPzG233ZYjjjgir776aqtlS5YsyZVXXpkrr7yyrDh626c+9al861vfyvLly18vW7FiRS699NJceumlHdb75Cc/WfZ735l+/frlhhtuyHve85785S9/abVs2bJl+cEPftAmcU9n3vjGN+aWW27JoEGDKh1qj2lqasqdd96ZO++8s6z6u+yySy677LIKRwUbttLS2wEA3Wv/8UltF3Jd1dYl+42vXDwAdF05x3bHcwCArnENBhuWyZ3fwLLBcBwDAABgTcbIAAAA2vXggw/mi1/8YpvyU089teQEFEnhoe2zzjqrTfl//ud/5le/+lXJ7Q0bNix333133vrWt5Zct7a2NhdccEG+/vWvl1x3zW1/+ctfTl1d5ebwHjJkSMXaojL69euXSy+9NNdee22GDRtWsXYHDx5csbZ6ypQpUzJ27NjeDoMO1NXV5Vvf+lYuuOCCkuodfPDBefDBB/Oud72rovH09j6+zTbb5KKLLurVGNa25ZZbZubMmRk/vmvjinvvvXfuv//+vPnNb65QZOufd7/73Zk5c2ZGjBjR26FAVancVS0A0HVDhydjxyX33lFe/bHjkqGVG8gAoEgNi5IZdyYL5iXLlyYDByfb75ykJfnbY8ngIcnihuLbczwHAOiacvrXrsF6RnvXzqPGFB7S8P5veJ55Mrn6kuRvjyar/v9Zmmr6JZsOT4ZtnqSluH1k1z2SQUOSZa/1WOhl22rb5IWnu6dtxzHoHc5t0Df4LAKwvunKuavYusbIAACAPuyXv/xlVqxY0a3bGDBgQJuyV155JUceeWQaGxtble+zzz759re/Xfa2Tj/99MycObPVLPSrVq3Kxz72sTz00EPZeuutS2pvm222yf3335+vf/3r+e///u828bZnr732yve+973su+++Jce/pvr6+nz729/Osccem29+85u58cYb09TUVHI7Q4cOzfvf//4cc8wxOeSQQ7oUE93nE5/4RN7//vfn/PPPzxVXXJGFCxeW3EZ9fX0OOOCAfPzjH89HPvKRboiye9XV1WXatGk55ZRT8sMf/jDNzc29HdJ6b+ONN86VV16ZW2+9NXfffXeWLFlSchv9+vXLoYcemvPPPz+77bZbWXG8+c1vzsyZM/PTn/40559/fubMmVNWOyNHjsxRRx2VY445JiNHjiyrjUo6/vjjM2zYsJx00kn55z//2dvhJEmGDx+eO++8M9dcc03OOuusPPHEE0XX3XrrrfOVr3wln/vc51JbW9uNUXaPr3zlK9luu+1y2223lfS617TjjjvmG9/4Rj7xiU+kpqamwhECNS0tLS29HQQAsIamxuSiM5JH/1xavZ12S077dtK/vnviAqCtpsZk6mXJrOlJ88rKtLnzW5NTz3U8BwDoqqbG5OIzCw8VrMvI0ckp57gG607runaurSs8rDHpBH+HDcGSV5NzT05efK74OuvaRxa+lHxlcrJqVcXCrLiRo5PPfT357unJ3x+tbNtvfkvyxW/5/EBPcm6DvsFnEYD1TVfOXeXUNUYGAADQp639wOz222+fp556qlXZP/7xj1x//fW5++678/DDD+fFF1/M8uXLs/HGG2fHHXfMvvvum49+9KN5z3ve0y0xvvzyy7nlllvym9/8JnPmzMmTTz6ZxYsXv768X79+2WSTTbLTTjtll112yZgxY3LggQdmr732Wi8fit6QLV++PHfffXfuuuuu/PGPf8yjjz6al1566fXlNTU1GTJkSLbddtvssssu2W233bL//vtn//33z+DBg3sx8sp57rnnMnXq1DzwwAOZN29e/vnPf2bJkiVZtmxZm3XvueeeHHjggT0f5Hqmqakpc+bMyX333Zc//vGPeeyxx/LEE0/k5Zdfzqo17vEYPHhwtttuu7ztbW97/bj2hje8oaKxzJ07N7fcckvuu+++PPzww3n22WdbJXaqr6/P5ptvnlGjRmWXXXbJO97xjhx88MHZdtttKxpHpTQ1NeWWW27Jr371q/zpT3/KU089lcWLF+e1115r9d4mySc/+clcddVVPRJXc3NzfvWrX+Xmm2/Offfdl0cffbTVeWPw4MHZaaed8s53vjMTJkzI+9///tTXV8eY5JNPPpnf/e53uf/++/PXv/41jz/+eJ599tlWSan69++fESNGZPTo0dlzzz3zgQ98IO9617t6MWqofpJpAEBf09SYXHh68tjDpdUbODj59lXJRpt0S1gArKWUG89K8ea3FJJp1LfNiA4AQIk8WNc3lPrQxslnux6uZkteTb78yaSx7Y0mReloH2lqTM7/UvLU/K7HWGlrHmsWvpSc8anKb+PNuyWnfstnB3qKcxv0DT6LAKxvunLu6mpdY2QAAAB9UjHJNPqixsbGLFu2LP3798+QIUN6Oxy60YoVK7J06dLU1NRko402Sr9+/Xo7JKrIa6+9lhUrVmSjjTZKXV1dj2+/paUlS5cuTVNTU4YMGVI1CR36omXLlmX58uWpr6/fIM8bTU1NWbp0aQYMGJBBgwb1djiwwZFMAwD6mmsuSe69o7y6W22bnH1FZeMBoH1dOV6vywGHJpOndE/bAAAbooZFycxpyfy5yfKlhYSUo8Yk+41Phg7r7eiqX6nXzq6Hq9uZn0leeLprbbS3j3RnH60cAwYm2++cvGWv1seazx7W/oNLleCzAz3HuQ36Bp9FANY3XTl3VeK8Z4wMAACgz1lfk2kAAMD6oufTNQEAHWtYWJgJpFwvPJ0882SyzZsqFxMAbXX1eL0us6Ynh0920xoAQKUMHZZMmFj4oWeVc+3serh6Pf1E1xNpJG33ke7uo5Vj5Yrks6e33o//eG/3JdJIkll3+exAT3Bug77BZxGA9U1Xzl1pqcx5zxgZAAAAAACwgenX2wEAAGuYMa3rN9T/7IrKxAJAxypxvO5M88rCrFAAALC+K+fa2fVw9arUuNXa+0h399HK0dzcdj++5tKe3yZQec5t0Df4LAKwvunKuct5DwAAAAAAoCySaQBAX7JgXtfb+NujXW8DgM5V4ni9LvPndv82AACgu5V77ex6uDr9/bHKtbXmPtITfbRyrL0fL13S89sEKs+5DfoGn0UA1jddOXc57wEAAAAAAJSlrrcDAADWsHxp19tYuaLrbQDQuUocr/vCNgAAoLuVe13rerg6VXLcas19pK/uL70RV199L6CaOLdB3+CzCMD6pjfOXc57AAAAAADABk4yDQDoSwYO7nobdf273gYAnavE8bovbAMAALpbude1roerU13/pHF5Zdpacx/pq/tLb8TVV98LqCbObdA3+CwCsL7pjXOX8x4AAAAAALCB69fbAQAAaxg5uuttbL9z19sAoHOVOF6vy6gx3b8NAADobuVeO7serk7bvblyba25j/REH60ca+/Hgzfq+W0ClefcBn2DzyIA65uunLuc9wAAAAAAAMoimQYA9CX7j09q67rWxlGfqUwsAHSsEsfrztTWJfuN7772AQCgp5Rz7ex6uHpVatxq7X2ku/to5aitbbsfT/5Cz28TqDznNugbfBYBWN905dzlvAcAAAAAAFAWyTQAoC8ZOjwZO678+lttm2zzpsrFA0D7unq8Xpex45Khw7qvfQAA6CnlXDu7Hq5e2+5YGL/qqrX3ke7uo5Vj7CFt9+O3H9C9ST/a2yZQec5t0Df4LAKwvunKuct5DwAAAAA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      "text/plain": [
       "<Figure size 4500x1500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cc.pl.draw_area(\"chr1\", 4856929, 4863861, 100000, peak_data, Brd4, \"mm10\", font_size = 2, \n",
    "                plotsize = [1,1,5], \n",
    "                figsize = (30,10), peak_line = 2, save = False, example_length = 5000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "29b845fc-22e5-42b7-8608-5c7bce72afc7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rtOa5557Lc889l9/+9rd573vfWxCC1Ba/+93vcuqpp7a57+uvv56xY8dm7Nix+fSnP52f/exnKw3BKdb999+fww47bJWhNWuiKVOm5Kijjspf//rXNm2/dOnS3Hnnnbnzzjvz3e9+NxdffHGGDRtW1pomTJiQMWPG5J///Ocqt/3HP/6RY445Jj//+c9z8803l3S/33HHHTnmmGNWGtrRmvnz5+fuu+/O3XffnW9+85u54447su+++xY9P7BiwjQAAICuZ9arybe/kix8o2V7U1OypDF56bnmf088nNx4VfMHYQd+MXl5RvOHbm3x+mvJ7y9/u/8hxyTdik/bBgAAqAqLG5NrL0om3lH4K1/vXHtVy9ppVdf3hn//Msi7f/FodW6LrnYbA/A2+wCgNaOPbvvnGoOHNr9GAAAAwOoYfXTy4nPJ9MfLN+byZckb85qPc33nmGTDTZKvn5fUd1u9Y2LWzV3arrvumh/+8IcFYRc//OEPs9tuu2XkyJFtGmfJkiU56KCDMmvWrBbtm222WS677LKS6/vRj36U//zP/yy6380335xddtkld955ZzbbbLNVd2jF9ddfnyOOOCLz588vqf8///nPfPazn833vve9nH766SWN8U6vvfZaPvrRj2bKlDZ+d7eDXHDBBTnxxBMLQlRW5o033sjnPve53HDDDfnkJz/5VvsNN9yQgw8+OIsXL27zWEuXLs3JJ5+c2trafPWrXy2q9jc9/vjjOeCAA0o+qX/evHn5xje+kb/97W+5+uqr07Nnz5LGeafzzjsvp556alG3a5Lcc8892WOPPTJ+/Piss846q11HtVq6dGkOOeSQXHfddUX1a2pqys9+9rPMmjUrV155ZZv7NTY2ZtSoUfnjH/9YbKkFli5duuqN3mHx4sX5yle+kssvv7zkOf/whz/kgQceyM0335ztt9++5HHedNNNN+Vzn/tc0aEia4Lf/va3OfLII7Nw4cKS+j/xxBPZa6+9ct555+X4448vS01jx47NF77whaJeW5Pksccey7BhwzJ+/PgMGjSozf2uvPLKHHnkkVm2bFmRlRYq9vEOrJowDQAAoGuZ9Wpy+phk+fK2bb9saXMC/cszkmO/mfzfZa1/ANeW/iedlTR0L712AACANdHixuT8M1b+ZcRqWju15fqu7Ms/pdwWXe02BuBt9gHAijR0b37Or+jEoiSpqxe2AwAAQHnV1LTv+C8/n/znmOS9g5Knnljxdqs6Jmbd3OWdfPLJGT9+fH7/+9+/1dbU1JQxY8bk4YcfzsCBA1c5xmmnnZa//vWvLdq6d++esWPHlnxC/+9///v813/9V4u2+vr6fPjDH86mm26anj175sUXX8xDDz2UV155paD/008/nf322y9//etf079//6Lmvvzyy/OlL30py1fw/dpBgwZl2223Tf/+/VNbW5t//etf+etf/5pXX321xXZNTU352te+lgULFuS///u/i6rhnZYtW5YDDjigIEhjgw02yI477pj11lsvSfLCCy/k8ccfz4IFC0qeqxh/+MMfCoI0+vfvnw9/+MPZYIMN0tTUlOeffz4TJ04sOGl++fLl+cIXvpB//OMf2WijjTJx4sQcdNBBWbJkyVvb9O7dO7vssks22mijdO/ePS+88EImTJjQasDJ//t//y/77rtvttlmm6Kuw6RJk7LvvvsWBMG8ad11182OO+6Y9ddfPz179syrr76aKVOmtBq88fvf/z4jR47MHXfckbq6uqLqeKcrrriiIOCmT58+2XnnnbPhhhumZ8+emTlzZu67775WH/uPPfZYTjrppNUKT6h2Rx11VEGQxkYbbfTW82n58uWZMWNG/vKXv7QainDVVVdln332yRFHHNGm+b72ta+tMEhjrbXWytChQzNo0KCstdZaSZI5c+bktddeyxNPPJGXXnqpuCv3DosXL86nPvWpjBs3rtXLu3Xrlu233z4DBw5Mv379Mm/evDz33HN54IEHWjwXk+Sll17KnnvumfHjx2e77bYruaZHHnkkhx56aIvXhJqammy33XbZfPPNs+6662b27Nl54YUX8vDDD5c8TyVcd911OfTQQ1e479hyyy2zzTbbZP31189rr72W6dOnZ/LkyQXbLV26NCeccEKamppywgknrFZNd955Zz7/+c+3uD979OiRnXfeOe9973uz1lpr5bXXXssDDzyQGTNmFPSfMWNGvvjFL+ZPf/pTatrw3nbSpEkrDNKoqanJ1ltvnS233DL9+/dP9+7dM3/+/MydOzfTpk3LtGnThGdAB6hpKjaqCwAAYE12woHJwjdK67vHx5MxJyZzZicTxiV3/zF5/bXi+wMAAHQlv/5p85cV22pNXzsVe31Xpq23RVe7jQF4m30A0BZvfq4xdXKyaEHSo1cyZNtktxFJ336Vrg4AAIBqUc7PSMppVcfErJs73F577ZV77rmnRdvhhx/e4SfBz5kzJzvuuGOeeuqpFu0777xzxo8fn4aGFYeoXH/99fnc5z5X0P7zn/88xx57bJvmf/cJuv37909dXd1bQQHdu3fPGWeckWOOOSbrrrtui22XLl2acePG5eSTT860adMKxv785z+fq666qk11JMkDDzyQ3XbbreBE8t69e+foo4/O8ccfn0GDBhX0W758ef70pz/l61//ev72t7+1uKy2tja333579tlnn1XOf/nll+fII49s0bbhhhvm5ZdffuvvfffdN//93/+dXXbZpeC2a2pqyvjx47PHHnsUjD1o0KA8++yzBdu3xbvn6devX2pra/Paa83fHd52223z/e9/PyNGjCgIkpgzZ06+/e1v56c//WnBuF/60pfyox/9KO9///vfCg3YbLPNcvbZZ+ezn/1sundvGQDU2NiYc889N9/85jcLTtbeb7/9Vhga0JrZs2dnhx12yDPPPFNw2UEHHZRTTjklO++8c6snkD/xxBM588wz87vf/a7gsm9+85ttCk955plnstlmm7Vo23TTTfPKK6+8FeAwdOjQfPe7380nPvGJdOvWrcW2y5cvz/XXX58TTzyx1cCFiRMn5iMf+Uircy9ZsiRz5sx56+8TTjgh1157bYttbrjhhgwbNmyV16Nv374FtZVTa7f/ZZdd1qYgi9aeT0OGDMnUqVPf+vuTn/xkvvWtb2WnnXYq6L9w4cKcd955+c53vlPwmtCvX7/MmDEjvXr1WmkN06ZNy9Zbb13weN1xxx1z5plnZr/99lvp7ffqq6/m9ttvz0033ZQbbrgha6+9dovXg5U58cQT87Of/aygfauttsp//dd/5aCDDmq1/nnz5uXCCy/M97///bz++usFfR966KFVXu+k9X3cO1/PevTokZNPPjlf/epXs+GGG7Zax7Rp07LDDjtk9uzZb92GEydOzAEHHNBi29GjR+eCCy5YZU09evR4K7Tk3d79WBs4cGCrrw+teeaZZ7Lddttl7ty5BZftv//+Oeuss1oNIZk2bVrOOuus/PrXvy64rFu3brnvvvuy4447tqmG1l6n6+vr39qXDho0KGeeeWZGjRqVnj17FvS/8847c9xxx+XJJ58suOw3v/lNDjnkkFXWsMcee2T8+PEt2vr06ZNvfvObOfLIIzNgwIAV9l28eHEeeOCB/PGPf8x1112Xp59+Orfeems+9rGPrXJeoO2EaQAAAF3H3yclP/la6f3r6pNzrmz+gGzOrOaE+9YS6dvSHwAAoCvoamunUq7vyrTltuhqtzEAb7MPAAAAAKCzKPdnJOXkmFin09qJxm09Ibgt+vTpUxBGsCKTJk3KRz7ykSxatKhF+/HHH7/CeqZPn54dd9yx4OTh0aNH55prrmlznSv7tfsBAwbkrrvuytChQ1c6xsKFCzN69OjceOONBZfddNNNGTly5CrreP3117P99tsXnDw9dOjQjB07NkOGDFnlGEuXLs1xxx2Xiy++uEX7RhttlKeeeqrVE5jfqbWT/9/pRz/6UU477bRV1tGacoZpvNPnP//5XHbZZasMVPjOd76TM888s0Vbjx49sv/+++e6665LkgwfPjz/93//t8KT3d90xRVXFIQp1NTU5KmnnioIqFiRz3zmM7nhhhtatPXr1y9XXnllmx4vSfKrX/0qX/nKV7J06duv+bW1tXnwwQezww47rLRva2Ea7/SlL30pF110Uerr61c6zlNPPZVhw4blX//6V4v2MWPG5IorrmjDtUiOOOKIgm3vvvvu7LXXXm3q357KHabxpvr6+vziF7/IUUcdtcpxbrzxxhxwwAEFz5df/epXK32+Jsl3v/vdfOtb32rRNmLEiNx4440rDSpqzaxZszJ27Nh85StfWeW2N9xwQz7zmc8UtB9//PH58Y9/3KZ9w/Tp0zNy5MiCcIWTTjop55133ir7t7aPe9NGG22U22+/PR/4wAdWOc67/fnPf85HP/rRFm3lCKIqNUyjqakpe+yxRyZMmFBw2fnnn58TT1x1uP+1116bL3zhCwWhK0OGDMmkSZNWue9IVv46PXLkyPz2t79N7969VzrGq6++mt133z3/+Mc/WrTvscceK7wv3/T8889n4MCBLZ4nffr0yV/+8pei7+fly5fnpptuypZbbpmtt966qL7AytVWugAAAIAO8+vClNmiLFvanECfJOPHFf/B3zv7AwAAdAVdbe1UyvVdmbbcFl3tNgbgbfYBAAAAAHQW5f6MpJwcE1sjXHvttVlvvfXK8q+YQIvtt98+P/tZ4XdL/+d//idjx44taF+0aFFGjRpVEKQxZMiQXHLJJcVf8VY0NDTk1ltvXWWQRpL07Nkzv/3tb7PLLrsUXHbGGWe0ab6zzz674MTpwYMH56677mpTkEbSfIL+RRddlE996lMt2l966aU2BxusyBlnnFFykEZ72XfffXPllVeuMkgjaa5/8ODBLdoWLVr0VpDGtttumz/+8Y+rDNJImk+c32effVq0NTU15Te/+U2b6r755psLgjR69eqVW265pc1BGknyxS9+MT/84Q9btC1fvjznnHNOm8dozahRo3LppZeuMkgjSbbYYouce+65Be3XXXddFi9evFp1VLOf/vSnbQrSSJJPfepT+fKXv1zQfvXVV6+yb2sBCz/72c+KDtJIkv79+7cpSGPx4sU5/vjjC9pPPvnkXHDBBW0OWXrf+96XW2+9Neuss06L9osvvjizZs1q0xit6d69e+64446SgjQ6o1tvvbXV+/nMM89sU5BG0hxCdeGFFxa0T506NVdeeeVq1bfrrrvmhhtuWGWQRtIcYPW///u/Be333ntvZsyYsdK+EyZMKAicOeGEE0q6n2tra/OpT31KkAa0A2EaAABA1/HazNUfY+rk5v8+OWX1+gMAAHQFXW3tVOr1XZlV3RZd7TYG4G32AQAAAAB0Fu3xGUk5OSbGShx11FE57LDDCtq/9KUv5cknn2zR9tWvfjWPPPJIi7aePXtm7NixbQpDaItTTjklO+20U5u379GjRy6++OLU1dW1aH/kkUdy//33r7Tv3Llzc/HFF7doq62tzTXXXJMBAwa0vegkNTU1ufTSS9OrV68W7eedd17BicZttc022+Rb3/pWSX3bS48ePXLFFVekpqamTdvX19fni1/84govv+KKK9p8kn+S/Md//EdB21//+tc29f3Rj35U0Hb22We3GsayKqeccko+9KEPtWi77rrr8txzzxU9VtJ8Mvull15aVJ+DDz44G220UYu2BQsW5LHHHiuphmo3fPjwHHvssUX1OfnkkwvaHnzwwVU+p1988cUWfw8YMKAgVKbcfvOb3+SFF15o0bb99tvnxz/+cdFjbb755jn77LNbtC1YsCAXXXRRyfV985vfzPvf//6S+3c2rQVRbbfddvnGN75R1DhHHXVU9t133zaN31bdunXLb37zmzYF87zpIx/5SHbeeeeC9gceeGCl/d79WH9zLKBzEaYBAAB0HU3LV3+MRQta/rfU/gAAAF1BV1s7tUfdqxqzq93GALzNPgAAAACAzqKzH3Pq7PVRcRdddFHBSc7z5s3LqFGjsnDhwiTJVVddlUsuuaSg789//vMMHTq0LHX06tUrX//614vuN3To0IwePbqgfVXhBJdeemnmzp3bom306NHZYYcdiq4hSdZbb70cfvjhLdqefPLJ/OMf/yhpvK9+9avp1q1bSX3by6GHHpr3vOc9RfXZb7/9Wm3fd99988EPfrCosYYPH17QNmnSpFX2e/jhh3PPPfe0aBs4cGCOP/74ouZ/p9NOO63F38uWLcvNN99c0ljHHnts1l577aL61NXVZf/99y9of+ihh0qqodp97WtfK7rP1ltvnS233LJF29y5czN9+vSV9lu6dOlK/24P5557bkHbD3/4w9TWlnYK9Re/+MX069evRdsf/vCHksbq2bNnjjvuuJL6dkbPP/98br/99oL2s88+uyDYqS3OOeecgrbHH388f/nLX0qq75BDDsmgQYOK7vfpT3+6oG1VryetPbaXLFlS9NxA+xKmAQAAdB01ZVgC9ejV8r+l9gcAAOgKutraqT3qXtWYXe02BuBt9gEAAAAAdBad/ZhTZ6+PiuvVq1euu+66rLXWWi3aJ0+enOOOOy5PPPFEjj766IJ+RxxxRI488siy1fGZz3wmffr0KanvmDFjCtreHZ7wbrfcckubxinGiBEjCtomTJhQ9Dh1dXU55JBDVquW9nDggQcW3Wfrrbdu9YT+z372s0WP1a9fv4IwjxdffDFNTU0r7dfafX3IIYekvr6+6BreNHz48ILrVcp9nSSjRo0qqd92221X0Pbiiy+WNFY1GzBgQPbaa6+S+pZyG2+wwQYt/n799ddbDV8olxkzZmTKlCkt2t7znvdkn332KXnMHj16ZM8992zRNmnSpCxYUHxA18iRI7POOuuUXEtnM378+ILXnA033DAf+9jHShpv++23z7bbblvQfu+995Y0Xke+nrz7sZ4kv/vd70qaH2g/wjQAAICuY931V3+MIf8+UDO4xBTxIYUHegAAAKpWV1s7lXp9V2ZVt0VXu40BeJt9AAAAAACdRXt8RlJOjol1eocffniamprK8u+II44oqYatttoqF198cUH7ZZddlj333DNvvPFGi/ahQ4fmF7/4RUlzrcjIkSNL7rvPPvukR48eLdqmT5+e1157rdXtlyxZkvvvv79FW7du3bL33nuXXEOS7LDDDgVt9913X9HjbL311ll77bVXq5b2sOuuuxbdp0ePHq2GpJQyVpKst956Lf5evnx55s2bt9I+rZ2U3lrwSTH69euXQYMGtWgr5b7u27dv3v/+95dUw0YbbVTQNmfOnJLGqmYf+chHUlNTU1LfUm7j1h7bhx12WO6+++6SaliV1h7frYW9FOvdr2dLlizJ3/72t6LH2WWXXVarjs7mL3/5S0Hbxz/+8dTV1ZU85gEHHNCmedpi2LBhJfUr12P9mmuuyRlnnJHFixeXVAdQfsI0AACArmPMV1evf119stu/DxzvPqL571L7AwAAdAVdbe1UyvVdmbbcFl3tNgbgbfYBAAAAAHQW5f6MpJwcE6MIhxxySI455piC9ldffbXF32uttVbGjh2bnj17lnX+7bffvuS+dXV1GTq0MNjm4YcfbnX7Rx55pCAgZMstt0y3bt1KriFJ1l133YK2F198sehxtt2284Xg9O7dO/369Supb2thGhtvvHHZxpo7d+4Kt29qamo15KLUAIt3evf9/dJLLxU9xnvf+96Sgx5aC1xZ2W3RVZX6WEtKu40PO+ywgiCLmTNnZu+9985uu+2WX/7yl3nhhRdKrundJk6cWNDWHo/vpHpez1bHpEmTCtpaC1IqRmv9V7T/WplevXqV/DpdymN9yJAhrYalnH322Rk0aFC+9rWv5YEHHsjy5ctLqgkoD2EaAABA17H19knP3qX3HzY86fvvgyt9+zf/XWp/AACArqCrrZ1Kub4r05bboqvdxgC8zT4AAAAAgM6i3J+RlJNjYhTpvPPOy4477rjSbS655JIMGTKkrPPW1tZm8ODBqzXGVlttVdD2yiuvtLrt888/X9D2xBNPpKamZrX+9e5d+D3dWbNmFX1dWjuJvdLWWWedkvvW1dWVbbzWxlq6dOkKt589e3bmz59f0L7++uuv9v394IMPthhz0aJFWbBgQVHXp9QT35Okvr4wyGllt0VX1dG38TbbbJPjjjuu1csmTpyYo48+OhtvvHG23HLLHHnkkfnlL3+Zxx9/vOQaW3s9+8///M/Vfny3dh2q5fVsdbS2X9lmm21Wa8zWwk/eHWTVFpV4PTn33HPT0NBQ0P7SSy/lBz/4QT784Q9n3XXXzciRI3PWWWflrrvuysKFC0uuEyheJ419BAAAaCdn/jL5rzFJU5HpnrV1yV/vTh6akLx3ULLxZsmLzyX19UlbDroOHpocUphWDkAXMWd2Mv625MkpyaIFSY9eyZBtm3/5xBc2gHLzmkNnM/ro5OUZzY/JVVmT105vPvdmvpT06JksWs0Pvrv3SP4+Kfn6F5uDIXv3WfFzuavcxgAUsg8AADqC400AALRFMceqVldNTdLUtOrtquWYmPfkHap79+4ZO3Zshg4dmjfeeKPg8mOOOSajR48u+7xrrbVWamtX73ezWwtneP3111vdtpQTwks1e/bsovusvfba7VDJ6mntROvONN6KdOR9nTTf37169Wrz9h11O3RllbiNzz333Lz66qu55pprVrjN9OnTM3369Fx++eVJmgNehg8fntGjR2fEiBHp1q1bm+byetaxWtuvrE7YUNJ6CEZjY2MWLlyYnj17tnmcSjzWd91111x11VU5/PDDVxiS8frrr+eWW27JLbfckiRpaGjILrvskgMPPDAHH3xwNthgg44sGboc7zQAAICuY3FjctPVbfsQ7d2WL0salyWNi5o/kCrmA78NN0mO/3bSrTBxFIAqt7gxufaiZOIdybJ3hS898XBy41XNv4ByyDH2E8Dq85pDZ9XQPTnprBU/PpOkrn7NfXyu7Lm3OhoXJa+83LJtRc/lar+NAVgx+wAAoD053gQAQDEauifHfjP5wanJy4W/EF9Wq/oOYLUcE/OevGIefvjhVoM0kmTrrbdulzn79Omz2mO0dsJ2ZwjTWLJkSdF9BCyUT0eHaZRyf1N96uvr85vf/CYf+9jH8s1vfjPPPffcKvvMnDkzV199da6++upstNFGOf3003P00UenoWHl+zivZx2rtf3K6gaGrKj/7NmziwrTqJRRo0bl/e9/f0477bTceuutq9x+8eLFuffee3Pvvffm1FNPzWGHHZZvfetbGTRoUPsXC11Qdb0KAwAArMjixuT8M9oWglHXLWlalixfXp65X34++Z8zm7/U3tC9PGMC0Pm1Zd+zbGly763Nv8xiPwGsDq85dHYN3ZMxJyafHpNMGJdMnVwdv5pVzFqzR89kw4HJM/9YvTlX9Fyu1tsYgFWzDwAA2oPjTQAAFGtxY/KL77Z/kMaK1NQmgz+QbLNDdRwT8568Yp566ql88YtfXOHl/+///b985CMfyY477ljWeRcvXrzaYzQ2Nha0de/e+uNC4EHX4b6mksaMGZPRo0fnpptuytVXX5277rprhSE/7/TSSy/lxBNPzK9//euMHTs2m2222Qq39RjvWA0NDQW3+eruw1bUf0X7sM5om222yS233JLJkyfn17/+dW688cZMmzZtlf2WLl2ayy67LGPHjs0vf/nLHHrooR1QLXQtwjQAAICu4dqL2nZyU5Isa4cDak9Oaa5hzInlHxuAzqmYfY/9BLC6vOawpujbLxk5uvlfNSjmubdoYfLs1PLNvaLncrXdxgC0nX0AAFBOjjcBAFCsYt5Dtoem5cmc2dVzfMx78opobGzMqFGjMnfu3FVu8/DDD2edddYp29wrm7Ot5syZU9DWr1/rwTK9evUqaNtxxx1z2223rXYd71ZXV1f2MWm71u7rJJkxY0a7nKjev3//so/Jmq2hoSGf/exn89nPfjbLly/PI488kokTJ+Yvf/lLxo8fnxdeeGGFfR966KHsu+++uf/++7Peeuu1uk1rj/Ef/ehHOeKII8p1FVY6V1fTr1+/vPHGGy3aVncf1tr+q6ampqz72Y6y7bbb5sc//nF+/OMf58UXX8z48eNz3333Zfz48Xn00UezbNmyVvvNnz8/X/jCF9LQ0JDPfe5zHVw1VDdhGgAAQPWbMyuZeEelq2iu4dNj1vzEewBWrZR9j/0EUCqvOVAZpTz3mprKW4PnMgAAAO3B8SYAAIrVWb6j9/LzyYx/Jhuv+Nfr1wjek1fMV7/61UyaNKlFW+/evdPQ0JDZs2e/1fbPf/4zRx55ZH7/+9+Xbe7GxsbMnj17heEXbfHyyy8XtK3oROSNNtqooG3u3LkZMGBAyfPTObV2XyfNJ6q7v+lotbW12WGHHbLDDjvkhBNOSJI89dRTuemmm3LNNdfkr3/9a0Gfp59+Ol//+tdzySWXtDrmRhttlMmTJ7doW7x4scd3O+nXr19mzJjRoq21/U8xWuvfp0+fNT6M6T3veU8OPvjgHHzwwUmSefPm5fbbb88NN9yQ6667LosWLWqxfVNTU44++ujst99+WXvttStRMlSl2koXAAAA0O7Gj0uWLa10Fc01TBhX6SoA6Ail7HvsJ4BSec2ByugMa03PZQAAANqD400AABSrM3xu8qbftX6i7RrFe/KKuPrqq3PxxRcXtP/yl7/MFVdckZqamhbtN9xwQ84999yy1vDII4+Uvf/73ve+VrfdcsstC9peeumlLFu2bLVqoPPZYIMN0qdPn4L2559/vgLVQKEtttgiJ554Yu6///5MmDCh1detyy+/PK+//nqr/Vt7PfP4bj8DBw4saFvd/dfDDz/cpnnWdH369MmBBx6YK6+8Ms8//3wOO+ywgm1ee+21/PrXv65AdVC9hGkAAADV78kpla7gbVMnr3obANZ8pe577CeAUnjNgcroLGtNz2UAAADKzfEmAACK1Vk+N0mSZ6dVuoLV5z15h/vHP/6Rr3zlKwXt//Ef/5HPf/7z+eQnP5nTTjut4PLTTz89999/f9nqWJ2xXnzxxYKTx9daa628//3vb3X7oUOHpkePHi3a5s+fn4ceeqjkGuicampq8qEPfaig/Z577qlANbByw4YNy5133pnevXu3aF+6dOkKH7M777xzQZvHd/vZZZddCtpWd1/YWv9dd911tcbs7AYMGJBf//rX+eQnP1lw2Z/+9KcKVATVS5gGAABQ/RYtqHQFb+tMtQDQfkp9vbefAErhNQcqo7M8hzpLHQAAAFQPx5sAAChWZ3ovuHRJpStYfd6Td6gFCxbkc5/7XN54440W7R/84Afz05/+9K2/v/e972W33XZrsc2SJUty8MEHZ9asWWWp5Zprrilr35122il1dXWtbt/Q0JC99967oP3GG28suQY6r4997GMFbV39vq6vry9oW758eQUq4d0GDhzYasDAs88+2+r2++23X2prW54q/fe//z3TplVBwNa/dabH60c+8pGCtj/96U955ZVXShpv0aJFuf7669s0TzU67rjjCtpW9FgHSiNMAwAAqH49elW6grd1ploAaD+lvt7bTwCl8JoDldFZnkOdpQ4AAACqh+NNAAAUqzO9F6zvVukKVp/35B3q2GOPzeOPP96ibe21187YsWPTo0ePt9rq6+tz7bXXZr311mux7XPPPZfDDjssTU1Nq13LlClTMmHChKL7LV26NJdccklB+2c/+9mV9vv85z9f0PY///M/ef3114uugc7t4IMPLghWmThxYv785z9XpqBOoE+fPgVtCxcurEAltGbQoEEFbQsWtB4atcEGG2SfffYpaD/77LPLXVbFdKbH66677pp11123RduK9kNtcfXVVxfsd7p165b99tuv1BLXKMU81oHSCNMAAACq3+Chla7gbUO2rXQFAHSEUvc99hNAKbzmQGV0lrWm5zIAAADl5ngTAADF6iyfmyTJwC0rXcHq8568w/zv//5vrrjiioL2Sy+9NO973/sK2t/73vfmqquuSm1ty1Pybrnllvzwhz8sS00nnHBCli1bVlSfn/70p5k6dWqLtl69emXMmDEr7Tdq1KhssskmLdrmzJmT4447rqj56fw23XTTfO5znytoP/bYYzNnzpwKVFR5a6+9dkHbiy++WIFKaM0LL7xQ0LbRRhutcPtTTjmloO2qq67KrbfeWta6KqUzPV579OiRL3/5ywXt3//+91u931bm9ddfz9e//vWC9lGjRq30/q4mxT7WgeIJ0wAAAKrf7iOSuvpKV9Fcw24jKl0FAB2hlH2P/QRQKq85UBmdYa3puQwAAEB7cLwJAIBidYbPTd500FGVrmD1eU/eISZPnpwTTjihoP3444/PqFGjVthvv/32a/XE3zPOOCPjx49f7boeeeSRHHvssW3e/q677so3vvGNgvbDDz88ffv2XWnfbt265Qc/+EFB+29+85uceuqpRYd6vNvzzz+fK6+8crXGoHy+973vpXv37i3a/v73v+czn/lMZs+evVpjz58/Pz/96U9Xa4yOtuWWheFLkyZNqkAl1eWNN97I9773vcyaNavkMV5++eX84Q9/KGjfbrvtVtjnYx/7WIYPH96ibdmyZRk9enTuvffekmt505133pkHHnhgtccp1SabbJIePXq0aHvssceyZMmSitRz7LHHplu3bi3a5s+fnwMPPDDz589v0xiLFy/OwQcfnJkzZxZcduKJJ5alzvZ2ySWX5OGHH16tMX75y18WtK3ssQ4UT5gGAABQ/fr2T4YNX/V27W3Y8KRvv0pXAUBHKGXfYz8BlMprDlRGKc+9mpry1uC5DAAAQHtwvAkAgGJ1lu/obbhJsvFmla5i9XXB9+RXXHFFampqyvbvgAMOWOl88+bNy6hRo7Jw4cIW7TvttFN+8pOfrLLeM888Mx/96EdbtL150nZrJwW3RW3t26f5XXzxxRkzZkxef/31lfa5/PLL8+lPfzqNjY0t2jfaaKN873vfa9O8hx56aD772c8WtJ977rnZZ599Mnny5DaN86bFixfnlltuySGHHJLNN988//u//1tUf9rP5ptvnh/96EcF7XfffXe233773HTTTWlqamrzeE1NTXnwwQdz6qmnZuONN85JJ51Uxmrb3/bbb1/QNnbs2Lz22msVqKZ6LFmyJN/4xjey6aab5thjj82ECROyfPnyNvd/9tlnM3LkyMydO7dF+9Zbb50PfvCDK+176aWXpl+/lvvCuXPnZu+99863vvWtzJkzp811JMlLL72UCy+8MNttt12GDx+eJ554oqj+5VRfX58PfOADLdrmzp2ba665piL1bLrppvnOd75T0P7Xv/41++23X5566qmV9n/hhRfyyU9+MrfffnvBZcccc0x23nnncpXarm6++ebsuOOO2XvvvXPVVVcV9RhbsmRJTj/99Pzud78ruOzQQw8tZ5nQ5XWS2EcAAIB2Nvro5OUZyZNTVr3t5lsnLz2bLFxQvvkHD00OOaZ84wHQ+RWz77GfAFaX1xyojGKfe58/Lvn20eWZ23MZAACA9uR4EwAAxSrmPWR76Nk7+fp5lZm7PXhP3q6OOuqoPPnkky3a1llnnfzud79LQ0PDKvvX1tbmmmuuyQc/+MG8/PLLb7W/+OKL+cIXvpDbbrutRThGW2yyySbZaaedcv311ydJrrzyyowbNy5f+MIXMnLkyGyyySbp2bNnXnrppdx///256qqr8sADD7Q61i9+8Yuss846bZ778ssvz7PPPpuHHnqoRfs999yT7bbbLnvvvXc+8YlPZNiwYdl0003Tr1+/1NXVZc6cOXn99dczffr0PProo/nb3/6W22+/PfPmzSvqutNxTjjhhDz++OP55S9/2aL92WefzSc/+clsvfXW+dznPpfddtstQ4YMSf/+/dOzZ8/Mmzcvc+bMyXPPPZfJkydn0qRJuf322zNjxowKXZPVt80222SLLbZocdL/q6++mp133jknnXRSdt1112y44Ybp0aNHQd++ffumW7duHVnuGueNN97IhRdemAsvvDAbbbRRRowYkR133DHbb799Nt544/Tr1y+9e/fOwoUL89JLL2Xy5Mm56aabcs011xQEBCXJOeecs8o5N9100/zf//1fPvaxj7UYY9myZfnud7+b8847L6NHj86ee+6ZnXbaKQMGDMg666yTRYsWZc6cOXn11Vfz2GOP5dFHH82ECRNy//33FxUw094++clP5m9/+1uLti9/+ct56KGHsv/++2eLLbbIWmutVbD/6dGjR9Zaa62y13P66afntttuy/jx41u033fffRk6dGjGjBmTUaNGZeutt86AAQMya9asTJ8+Pddff30uu+yyVoMnttpqqzaFWnU2d999d+6+++40NDRk7733zi677JIddtjhrdfRddZZJ8uWLcvs2bPz5JNP5u67787ll1+eZ555pmCsAw88cI0JE4E1hTANAACga2jonpx0VnLtRcnEO5JlSwu3qatvTmc/5JikcVHyg1OTl59fvXnfOWa3VX/AAkAVKXbfYz8BrA6vOVAZpTz3zv5V8q3/aH3btvBcBgAAoCM43gQAQLHa8h6ypjbp0TNZ+EZ5595wk+YgjV7lP1G0Yrwnbzc///nP89vf/rag/bLLLstmm23W5nE22GCDXHPNNdl3332zbNmyt9rvuOOOfPe73823v/3tomu75JJL8thjj2Xq1KlJkpkzZ+bcc8/Nueee2+YxzjzzzBxwwAFFzdunT5/ccccd+fSnP11wUnSS3HXXXbnrrruKGpPO6xe/+EUaGhpywQUXFFz297//Pd/97ncrUFXHq6mpyTHHHJPTTjutRfvTTz+dr371qyvte/fdd2evvfZqx+qqy0svvZTLL788l19+eUn9TzvttOy///5t2navvfbKzTffnM9+9rOZO3dui8vmz5+fSy+9NJdeemlJdVTaF7/4xXz/+9/PokWL3mpbsmRJfvazn+VnP/v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      "text/plain": [
       "<Figure size 4500x1200 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cc.pl.draw_area(\"chr2\", 6136575, 6144043, 75000, peak_data, Brd4, \"mm10\", font_size = 2, plotsize = [1,1,5],\n",
    "                figsize = (30,8), peak_line = 1, save = False, example_length = 5000)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87479aa1-f647-477b-b538-1733f26cb2f8",
   "metadata": {},
   "source": [
    "We can also visualize our data directly in the [WashU Epigenome Browser](http://epigenomegateway.wustl.edu/browser/). This can be useful for overlaying your data with other published datasets. Notice that this link only valid for 24hrs, so please rerun it if you want to use it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4232e722-cbd6-4a92-8a62-a30686a39b42",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "All qbed addressed\n",
      "All bed addressed\n",
      "Uploading files\n",
      "Please click the following link to see the data on WashU Epigenome Browser directly.\n",
      "https://epigenomegateway.wustl.edu/browser/?genome=mm10&hub=https://companion.epigenomegateway.org//task/544b112245ab68df385f75da9d4bfd8b/output//datahub.json\n"
     ]
    }
   ],
   "source": [
    "qbed = {\"Brd4\": Brd4}\n",
    "bed = {\"peak\": peak_data}\n",
    "cc.pl.WashU_browser_url(qbed = qbed, bed = bed, genome = 'mm10')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5b2fbc9-f6e5-491a-9067-d092032bd2f5",
   "metadata": {},
   "source": [
    "Pycallingcards can be used to visual peak locations acorss the genome to see if the distribution of peaks is unbiased and all chromosomes are represented."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "86d1a59b-3536-4c2e-a5b0-17a82e834af6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 15000x7500 with 21 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cc.pl.whole_peaks(peak_data, reference = \"mm10\", linewidth = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6f5f2dc-e8e6-4ba8-ab65-3340fa436901",
   "metadata": {},
   "source": [
    "For differential peak calling, we recommend first combining the data and calling peaks together (and then splitting the data and looking for enrichments under the jointly called peaks). However, it is often of interest to call peaks in each sample to analyze them separately or to then merge these peak calls using [pybedtools](https://daler.github.io/pybedtools/). Below is the code to do this:\n",
    "\n",
    "```python\n",
    "import pybedtools\n",
    "peak_data1 = cc.pp.call_peaks(Female_Brd4, method = \"CCcaller\", \n",
    "                              reference = \"mm10\", pvalue_cutoffbg = 0.1, \n",
    "                              maxbetween = 2000, pvalue_cutoffTTAA = 0.001, \n",
    "                              lam_win_size = 1000000,  pseudocounts = 0.1, record = True)\n",
    "peak_data2 = cc.pp.call_peaks(Male_Brd4, method = \"CCcaller\", \n",
    "                              reference = \"mm10\",  pvalue_cutoffbg = 0.1, \n",
    "                              maxbetween = 2000, pvalue_cutoffTTAA = 0.001, \n",
    "                              lam_win_size = 1000000, pseudocounts = 0.1, record = True)\n",
    "peak = cc.rd.combine_qbed([peak_data1, peak_data2])\n",
    "peak = pybedtools.BedTool.from_dataframe(peak).merge().to_dataframe() \n",
    "peak_data = peak.rename(columns={\"chrom\":\"Chr\", \"start\":\"Start\", \"end\":\"End\"})\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6cc472e-8033-4218-84d7-14cd9fb42b04",
   "metadata": {},
   "source": [
    "In the next step, we annote each peak to annotate using [bedtools](https://bedtools.readthedocs.io/en/latest/) and [pybedtools](https://daler.github.io/pybedtools/).\n",
    "Make sure they are all previously installed before using."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b9667e0d-1c52-4f90-8dad-14ced2da1973",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "In the bedtools method, we would use bedtools in the default path. Set bedtools path by 'bedtools_path' if needed.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Chr</th>\n",
       "      <th>Start</th>\n",
       "      <th>End</th>\n",
       "      <th>Experiment Insertions</th>\n",
       "      <th>Reference Insertions</th>\n",
       "      <th>Expected Insertions</th>\n",
       "      <th>pvalue</th>\n",
       "      <th>pvalue_adj</th>\n",
       "      <th>Nearest Refseq1</th>\n",
       "      <th>Gene Name1</th>\n",
       "      <th>Direction1</th>\n",
       "      <th>Distance1</th>\n",
       "      <th>Nearest Refseq2</th>\n",
       "      <th>Gene Name2</th>\n",
       "      <th>Direction2</th>\n",
       "      <th>Distance2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>4196775</td>\n",
       "      <td>4198714</td>\n",
       "      <td>16</td>\n",
       "      <td>12</td>\n",
       "      <td>0.142389</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NM_001195662</td>\n",
       "      <td>Rp1</td>\n",
       "      <td>-</td>\n",
       "      <td>92132</td>\n",
       "      <td>NM_011283</td>\n",
       "      <td>Rp1</td>\n",
       "      <td>-</td>\n",
       "      <td>144793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>4785068</td>\n",
       "      <td>4786551</td>\n",
       "      <td>17</td>\n",
       "      <td>15</td>\n",
       "      <td>0.572576</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NR_033530</td>\n",
       "      <td>Mrpl15</td>\n",
       "      <td>-</td>\n",
       "      <td>0</td>\n",
       "      <td>NM_008866</td>\n",
       "      <td>Lypla1</td>\n",
       "      <td>+</td>\n",
       "      <td>21342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>4806673</td>\n",
       "      <td>4807730</td>\n",
       "      <td>21</td>\n",
       "      <td>12</td>\n",
       "      <td>0.477937</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NM_008866</td>\n",
       "      <td>Lypla1</td>\n",
       "      <td>+</td>\n",
       "      <td>163</td>\n",
       "      <td>NR_033530</td>\n",
       "      <td>Mrpl15</td>\n",
       "      <td>-</td>\n",
       "      <td>-20948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>4856928</td>\n",
       "      <td>4862019</td>\n",
       "      <td>104</td>\n",
       "      <td>44</td>\n",
       "      <td>1.490080</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NM_011541</td>\n",
       "      <td>Tcea1</td>\n",
       "      <td>+</td>\n",
       "      <td>0</td>\n",
       "      <td>NM_008866</td>\n",
       "      <td>Lypla1</td>\n",
       "      <td>+</td>\n",
       "      <td>-10194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>4912814</td>\n",
       "      <td>4916593</td>\n",
       "      <td>7</td>\n",
       "      <td>22</td>\n",
       "      <td>0.791756</td>\n",
       "      <td>1.900897e-06</td>\n",
       "      <td>1.024407e-04</td>\n",
       "      <td>NM_001290372</td>\n",
       "      <td>Rgs20</td>\n",
       "      <td>-</td>\n",
       "      <td>0</td>\n",
       "      <td>NM_011541</td>\n",
       "      <td>Tcea1</td>\n",
       "      <td>+</td>\n",
       "      <td>-14906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24546</th>\n",
       "      <td>chrX</td>\n",
       "      <td>169936677</td>\n",
       "      <td>169937745</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>1.189526</td>\n",
       "      <td>3.479200e-05</td>\n",
       "      <td>1.673495e-03</td>\n",
       "      <td>NM_010797</td>\n",
       "      <td>Mid1</td>\n",
       "      <td>+</td>\n",
       "      <td>0</td>\n",
       "      <td>NR_029457</td>\n",
       "      <td>G530011O06Rik</td>\n",
       "      <td>-</td>\n",
       "      <td>37298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24547</th>\n",
       "      <td>chrY</td>\n",
       "      <td>897430</td>\n",
       "      <td>899700</td>\n",
       "      <td>11</td>\n",
       "      <td>24</td>\n",
       "      <td>0.528165</td>\n",
       "      <td>6.046275e-13</td>\n",
       "      <td>5.162843e-11</td>\n",
       "      <td>NM_011419</td>\n",
       "      <td>Kdm5d</td>\n",
       "      <td>+</td>\n",
       "      <td>0</td>\n",
       "      <td>NM_011667</td>\n",
       "      <td>Uba1y</td>\n",
       "      <td>+</td>\n",
       "      <td>-53207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24548</th>\n",
       "      <td>chrY</td>\n",
       "      <td>1009018</td>\n",
       "      <td>1011799</td>\n",
       "      <td>27</td>\n",
       "      <td>25</td>\n",
       "      <td>0.489073</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NM_012011</td>\n",
       "      <td>Eif2s3y</td>\n",
       "      <td>+</td>\n",
       "      <td>0</td>\n",
       "      <td>NR_027507</td>\n",
       "      <td>Tspy-ps</td>\n",
       "      <td>-</td>\n",
       "      <td>43965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24549</th>\n",
       "      <td>chrY</td>\n",
       "      <td>1243715</td>\n",
       "      <td>1246316</td>\n",
       "      <td>24</td>\n",
       "      <td>29</td>\n",
       "      <td>0.504932</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NM_009484</td>\n",
       "      <td>Uty</td>\n",
       "      <td>-</td>\n",
       "      <td>0</td>\n",
       "      <td>NM_012008</td>\n",
       "      <td>Ddx3y</td>\n",
       "      <td>-</td>\n",
       "      <td>14399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24550</th>\n",
       "      <td>chrY</td>\n",
       "      <td>1282482</td>\n",
       "      <td>1287504</td>\n",
       "      <td>19</td>\n",
       "      <td>60</td>\n",
       "      <td>0.945958</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NM_012008</td>\n",
       "      <td>Ddx3y</td>\n",
       "      <td>-</td>\n",
       "      <td>0</td>\n",
       "      <td>NM_148943</td>\n",
       "      <td>Usp9y</td>\n",
       "      <td>-</td>\n",
       "      <td>11457</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24551 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Chr      Start        End  Experiment Insertions  \\\n",
       "0      chr1    4196775    4198714                     16   \n",
       "1      chr1    4785068    4786551                     17   \n",
       "2      chr1    4806673    4807730                     21   \n",
       "3      chr1    4856928    4862019                    104   \n",
       "4      chr1    4912814    4916593                      7   \n",
       "...     ...        ...        ...                    ...   \n",
       "24546  chrX  169936677  169937745                      7   \n",
       "24547  chrY     897430     899700                     11   \n",
       "24548  chrY    1009018    1011799                     27   \n",
       "24549  chrY    1243715    1246316                     24   \n",
       "24550  chrY    1282482    1287504                     19   \n",
       "\n",
       "       Reference Insertions  Expected Insertions        pvalue    pvalue_adj  \\\n",
       "0                        12             0.142389  0.000000e+00  0.000000e+00   \n",
       "1                        15             0.572576  0.000000e+00  0.000000e+00   \n",
       "2                        12             0.477937  0.000000e+00  0.000000e+00   \n",
       "3                        44             1.490080  0.000000e+00  0.000000e+00   \n",
       "4                        22             0.791756  1.900897e-06  1.024407e-04   \n",
       "...                     ...                  ...           ...           ...   \n",
       "24546                     8             1.189526  3.479200e-05  1.673495e-03   \n",
       "24547                    24             0.528165  6.046275e-13  5.162843e-11   \n",
       "24548                    25             0.489073  0.000000e+00  0.000000e+00   \n",
       "24549                    29             0.504932  0.000000e+00  0.000000e+00   \n",
       "24550                    60             0.945958  0.000000e+00  0.000000e+00   \n",
       "\n",
       "      Nearest Refseq1 Gene Name1 Direction1  Distance1 Nearest Refseq2  \\\n",
       "0        NM_001195662        Rp1          -      92132       NM_011283   \n",
       "1           NR_033530     Mrpl15          -          0       NM_008866   \n",
       "2           NM_008866     Lypla1          +        163       NR_033530   \n",
       "3           NM_011541      Tcea1          +          0       NM_008866   \n",
       "4        NM_001290372      Rgs20          -          0       NM_011541   \n",
       "...               ...        ...        ...        ...             ...   \n",
       "24546       NM_010797       Mid1          +          0       NR_029457   \n",
       "24547       NM_011419      Kdm5d          +          0       NM_011667   \n",
       "24548       NM_012011    Eif2s3y          +          0       NR_027507   \n",
       "24549       NM_009484        Uty          -          0       NM_012008   \n",
       "24550       NM_012008      Ddx3y          -          0       NM_148943   \n",
       "\n",
       "          Gene Name2 Direction2  Distance2  \n",
       "0                Rp1          -     144793  \n",
       "1             Lypla1          +      21342  \n",
       "2             Mrpl15          -     -20948  \n",
       "3             Lypla1          +     -10194  \n",
       "4              Tcea1          +     -14906  \n",
       "...              ...        ...        ...  \n",
       "24546  G530011O06Rik          -      37298  \n",
       "24547          Uba1y          +     -53207  \n",
       "24548        Tspy-ps          -      43965  \n",
       "24549          Ddx3y          -      14399  \n",
       "24550          Usp9y          -      11457  \n",
       "\n",
       "[24551 rows x 16 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "peak_annotation = cc.pp.annotation(peak_data, reference = \"mm10\")\n",
    "peak_annotation = cc.pp.combine_annotation(peak_data, peak_annotation)\n",
    "peak_annotation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef1bc759-6e03-45c7-95b4-fdbfe19141b3",
   "metadata": {},
   "source": [
    "Use qbed data, peak data, and barcode data to make a group by peak [Anndata](https://anndata.readthedocs.io/en/latest/) object.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5ce9d309-8726-4fd4-b45f-81fdf0c8c9db",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 21/21 [00:07<00:00,  2.64it/s]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 2 × 24551\n",
       "    var: 'Chr', 'Start', 'End', 'Experiment Insertions', 'Reference Insertions', 'Expected Insertions', 'pvalue', 'pvalue_adj', 'Nearest Refseq1', 'Gene Name1', 'Direction1', 'Distance1', 'Nearest Refseq2', 'Gene Name2', 'Direction2', 'Distance2'"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata_cc = cc.pp.make_Anndata(Brd4, peak_annotation, [\"Female_Brd4\", \"Male_Brd4\"], key = 'group')\n",
    "adata_cc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "0e029f45-ed6d-479b-82fe-f3f5ae83e49a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Female_Brd4</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Male_Brd4</th>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: []\n",
       "Index: [Female_Brd4, Male_Brd4]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata_cc.obs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "dabb59eb-9413-49a4-adb1-c3483d91c8ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 2 × 24551\n",
       "    var: 'Chr', 'Start', 'End', 'Experiment Insertions', 'Reference Insertions', 'Expected Insertions', 'pvalue', 'pvalue_adj', 'Nearest Refseq1', 'Gene Name1', 'Direction1', 'Distance1', 'Nearest Refseq2', 'Gene Name2', 'Direction2', 'Distance2'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata_cc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "016670cf-f297-4e0b-8e8b-659b2ed0c275",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 24551/24551 [04:44<00:00, 86.27it/s] \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 2 × 24551\n",
       "    var: 'Chr', 'Start', 'End', 'Experiment Insertions', 'Reference Insertions', 'Expected Insertions', 'pvalue', 'pvalue_adj', 'Nearest Refseq1', 'Gene Name1', 'Direction1', 'Distance1', 'Nearest Refseq2', 'Gene Name2', 'Direction2', 'Distance2', 'Chr_liftover', 'Start_liftover', 'End_liftover'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata_cc = cc.tl.liftover(adata_cc)\n",
    "adata_cc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "362ff002-92d8-43f3-aacf-9c6ebc66fc42",
   "metadata": {},
   "source": [
    "Differential peak analysis will find out the significant binding for each group. In this example, we use the *Fisher's exact test* to find out."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "25ac3b84-2dac-4308-8bca-5daa00397877",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 2/2 [01:43<00:00, 51.87s/it]\n"
     ]
    }
   ],
   "source": [
    "cc.tl.rank_peak_groups(adata_cc, 'Index', method = 'fisher_exact', key_added = 'fisher_exact')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ccf75824-b658-4d7b-b08a-49f2cdb2cc1f",
   "metadata": {},
   "source": [
    "Plot the results for differential peak analysis.\n",
    "\n",
    "```python\n",
    "cc.tl.rank_peak_groups(adata_cc, 'Index', method = 'fisher_exact', key_added = 'fisher_exact', \n",
    "                       rankby = 'logfoldchanges')\n",
    "cc.pl.rank_peak_groups(adata_cc, key = 'fisher_exact',rankby = 'logfoldchanges')\n",
    "\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "06091dec-a458-4f2f-b614-6665b315c084",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1280x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cc.pl.rank_peak_groups(adata_cc, key = 'fisher_exact', rankby = 'pvalues')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ef3c054-8b27-48f4-9642-bd154bfc7879",
   "metadata": {},
   "source": [
    "We can use Pycallingcards to look at the insertion densities at peaks that are differentially bound.  In the plot below, we first plot female peaks as blue points and male as grey points, and then we plot male peaks as red and female peaks as grey.  From the plots below we can see there is much more Brd4 binding at this locus in females than in males.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e0910079-3577-47c1-897e-f110d37e516f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PlZaWqr6+3tUgpnwJrPc6SCsde5teth3GTKBhaWcSy2GS1dMrv2aaWLt2ra+Db8rKyrISqCtZwboDBw50vF5jY6NxsNLKlSvjfl+zZo2qqqo6ZfM1GQgTjUbpZwcsjIPJnGb+Dmvfw019m3isI5GIampqMga+20wHmEnK+9k+gCC5CbQP07WhSSKZMMwcU1VVpTVr1mRcLhKJhLKeBwAAAACET/ieyiAwhTClMQDkI7+m8F2/fr3Wr18fugfBXtsMN1mzuhK/gnzC+oAY4RCGbDVebbvttlq8eLHn7fgd7JEpU5BfKisrVV5e7ihYIl+ZPJjOlGHUr8yVYeIm4D4XQZHNzc1atmyZiouLXWUBixXmz9GPQVrp2PWx23rZJLAhW/VXrLC0M4nlMMnq6QevM03U1dVp3bp1Rsuanv+mQSp+cJsd32sgsR2AnRisa7pd+tnBMf1OeJ1ZwQm3mb/D1ma5rW/t975q1apOgxdSBb7Hss+RlStXduoH2IOAwxigDYSJaR00YMAA9erVK2v9OBOmiWT8mjnGS3+2uLhYVVVVxgO1eLYGAAAAAMgkHE9AkBXc5ASA3PB7Ct+wPQj2+t78yIBZqIII8uHBAZIJQ7Yar7xm947lV51tkinIL8n2VVNTE6qBHW4lPlz14/PxK3NlmLgJuM9lUKTXIF0pvJ9jNBpVdXV1oPuwPzu3MxNkCmzIZv0Vy6Q9yobEYH+/+/NBcDo40PT8Ly4uVv/+/bVhwwa3RTNmOsV0EGpqajR48OD2AS6RSMTxe6af7b9szfrgJJDL7b7C1maVlpaqpKQk4+CmRN26dUsapGuzB41VVFSkPZbJ+gF2xvz+/fsblSXs9TIQFNM2vKysLDR1juQ8kYzXmWP86M/aAw9MgnV5tgYAAAAAyIRA3S6kEKY0BoB8FFS9GpYHwV6D49wGmOQjJw+A/crEnIgHB0jGr2w1ueTntNybN29WY2OjUbadVOe1aaYgN9tO5Me+wsqvrOLJeM1cGSsXmUcTmQQ4lpSUqE+fPnHr5Ds/P0e/NDU1OQ58csr+fgUx7XEu6xST9igbEvvZ2bpP4iULupNgYqeDb4YNG6aWlhY1Nja6LZ6RqqoqV+uVlpZq/fr1nvdfU1OjgQMHtv/sVD70s8PQXjlhGrztJcjbaSCXl0EuYWqz6uvrHbdV3bt3V+/evbVs2bKM266vr5fU+ViaXOeaZjAPSxZ2INtM+v32+VFbWxua+t5NIpnKykpVVFQ4brv87M8OHTpUPXv2NBqIx7M1AAAAAEA63M3qQgphSmPkXr491AHCIKh6NSwPgr3WAb179/apJOGW7gFwsocOQWZuy+bUsMgfXrPV5Jqf58v69eu1fv16devWTUOGDGl/CJrY90l1Xg8ZMkSrV69Ou49Mgy1Mg0acZiXKJ0FkFQ9CrjKPJjIJcGxra9PSpUvby9aVBsv4Ld11UdDBjFJHnWda91VUVKh///4Zr99M6pRVq1appKQk6Xv343oxXXvUq1cvNTQ0ONqeG1u3btX69es1YMAAFRUVZe0+SY8ePVyv66QddDP4Zvjw4friiy+0adMmp0UzUlVV5TpQ2a/BOrF9ZLf95TAH6Ji0V2G752M6KNTt4FE3gVyxA17yVSQScZX5fciQIY4zTSceS5Pr3La2tozZfsM+2wcQJJN+fzQajQuqz8X1SSK3iWSKiooc3fsM4hrZtOwtLS1GywEAAAAAuiYiMruQQpjSGLkVliAEIN8EOYVvGB4Eey3DgAEDfCpJeGV6AJz4ELJbt26qqKgIrDxh+N4gOF4CLNxmqwmDIIKoWltbtWLFik77sae/THVeJ66TTLrBFk6CRtxkJcoHQWUVj+X0uifZuVVfXx+qbMaVlZVqbm5OmwkytmyF8CA5F9evYbgusus802yILS0t2rRpk/r06ZO2TjepU1pbW+MCP0pKSjRs2DBJnYNr3R6XZO2Raf3qlzVr1qimpkZDhw71lOnWCS8zVZi2gxUVFa6/p15n0kilqqqqvW3NJLEu7tOnj6vst8nEZmV1218O6+B3k76F5N857BfTwPBNmzapvLzc0bbdBnI1Nzc72k+sMNxzraur08qVKxWJRIzXiR24t3z5clf7tY+lnWk3k759+6Y9t8M+2wfgt0gkopqaGm3dulXdu3dXVVWVtttuu071tn1/KbGPGIbZVkwHwSQu5/Qeh5Nr5NiB8na/orm5udO+TOtMJ3UrAAAAAKDrCefdYwSiEKY0Ru4U8pTKQNCCnMI3DA+CvZahoaGhoOsPkwfAyR6gOM1U5EQYvjcIhh/BY06z1YRFaWlpxsxbfogNsPdjW4mcBo24zUoUJskevAaZVdzmJFgm2bll8h3Idjbjuro644C1lStXhiJgyIuSkpKs11cm10WlpaVav359YGVwM8B28+bN2rx5s9asWZM2KNLNedfW1payn+vlejG2PVq1apVvwZhO2OXv379/Vva3efNmx8GGNtMsn/X19aqrq3P8eUSjUV+ycI8ZM0Zr165VS0uLevTooSFDhhi3qcnq4uLiYt+yg9ufc11dnXEwYaxcDn5PFsBlB5ib9C2qq6uT9qFyfc/HbVCXCbeDndxmTc9Fm5XI6WwF/fr1U2VlZVxQnNs+zdatW9XY2Kja2lqj5cvLy9WnT5+8ne0D+SlsWcVtyfpBdp9uzJgx7WUuKSnRypUr027Lr+sTN8fKzYyPbu5xmPZnGxoatGLFirTLxw7UBQAAAADAK6I0uph8n9IYuVHIUyoD2ZKq/vUSVFZSUhKKABuvU3+uWrWqoOuPbASbORW28sC92IdjW7Zs0bp16zotk+sAi2wpKipS//79kx6DIPgREJzsQaXToBE3DzvDJNWD1yCzituam5uNAmZSBbWYfAeymc3YaRbiSCQSeGB70Pr27ZvV/oPpddGoUaNUXFwcWEat2H6Tm36YHeiRLOggqLrCy/VibW1tToJ0Y23cuDEr+3ETbGhzkuXT6edRV1eXMpDTqc8//7x9O01NTWpoaGgPtkkX9JOqLvbzPNu0aZNKS0tdZ3TP1eD3dAFcQ4cONepbZPpsC/GeT7YHOw0bNiynx8/NbAU9evSI68O4DWK3NTU1GZ2z9r2OoqKivJ3tA/knDDMmJJNusFJin66xsTErs624PVaxmevTsZdzmzjEtD9r0r+092U6G1iuB2QAAAAAAMItnE9rEah8ntIYuVGoUyoD2Zas/u3Tp48WLVrkWxaoXPAy9adk3fQu5PojjEGxYQ3YgzPJHo6lE2SARVgyD+VT0GGqrHtOg0ZKS0szBgSGZWBHonQPXoPMKh67n0yi0aiqq6sD348f3AwMyfepWevr67MSGGfXcabBD83Nzdpmm20CmU1Bin/fbgNIa2pqNHjw4PaMm7bS0lJ169bN9++t2+vFaDSaMTNcNmSrr24awJKMk8/MyefhNANnJqmm4m5ublZdXV3SoJ+KigrXwbNO2Nclbr7/VVVVOQnkMgng6t27t+f95OqeT8+ePX1dLpbbwU5BZ00Pipvvdmyd5HddkE7sQJx8ne0D+SWsM8nZ2dLTie3TZWMAgtNjFXuvILHfmUqfPn2MBhesWLFCLS0tcVnkJbNrZKdqa2szJlsI63U3AAAAACA8iNLoorjJCScKYUplICzs+te+UV1XV+d6W21tbaEIcPWS+ctWyPVHGINikwWBhCXQEmbcPCgPKsAiLJmHotGo8VS6YZAqaDpsGXKDqhvcZHXzm8kxbGpq8hwAnq3Pym1bWlRU5DgI0cuMAH7KRuCY00ERkvVZ9O3bV83NzYFkgrXfd2lpqRoaGlxvp6amRgMHDox7raioSEOHDg0kGMvt1PT5PKDNqf79+7te12ldYzpYIVuB0snOFTvoZ+DAgVm5XvByXVNTU6M+ffpkte9jGsC1ww47+LK/XFyzmdZxtbW1qqqqctRHMRmYkGxgldsgrFxnJW5paXG8jl2v+DFwqfv/Z+/O46Oq7v+Pv2eyQRKSkBASwhYQsSxa1IKoWKCI4kJtsV/FHRB3W0WrlWordf1qrdpWrYoLFLeqdWlFcGUTqYpaAUUEMSCEhOwhG2SZ3x/85n4nyUzm3pl7ZybJ6/l48GBmcufeM3c599x7P+dzEhKUmppqKsi5V69eYS0LsCKWR5Iz2470tumcvpY0s6727NmjuLg4Y9SfiooKy+ePsrIyNTc3B/2ex+NRcXFxqyzy3s/t7pDY1NSktLS0DrOKR3q0DwAAAABA5xN7kSMAYk6sBYwAnV0oAR8dzau+vl4JCQlRC66043fExcXZUJLY5FRmulD5e9hsJdCSgN7oCyfA0e79MJYyD5kdSjdWBMoEajVD7t69e4P+7lA7djgZhB1qxkJfWVlZqqysDClgNFBG47ZqampCKVorkQoyDCXALCEhQdnZ2ZaDMjMyMtSrVy81NTWpvr7eUjBqSkqKUlJSjAfw4QplPzJ7Lgs1e2B8fLyqqqocCdL18mb+DIfvPuO7Tvbv3x9u8fyqq6tT7969LX0nVtpPkVJfXx9y4HlycrKl6c1ktaupqYmJc2sksqxLB4/dcO5reAO5JEWkvWy2jikvL7elg0Wk7/ns2bPHdD3X0NCgLVu2GG0UM/W8y+VSenp6h+vRX2BeqCPKRHskqvr6esvf8e4zdnRcys3NDTk4GnBSLI8kZ7Z9753O6WPMzLpqampSQUFBSPP3Ki4utvwdb13er18/x9rgwa4NKysrHR3tg/txAAAAAND5EVUHIChupAP2sXu4yLbDHUcji2U4Q/R67d69O+LljpTq6uqYCHDwavvQwEqgZaxkTu3uwglwtDPAItYyD3W2YK6OHvaaXV8ej8f0Q0ir68fpIGy7tleoQbBOPkBtq7a2NuzMcGYeyoZyfPfu3dsIKtu1a1dI69Nq4E5tba1qa2tND30bjNXfbfZcFmqnCJfLpeTkZH399deWv2uFHcG03nVnZycyu3W3zqDhZHS1GjxoZh8KNxjcLpHK4B0fH2854NlXY2Oj9u7d2y57YLjt5UDnALP7SziZt70ifc9nz549lgOtvG2Uuro6VVVVmarng41w469jVTh1ZSzWsx3xtuXD6biUkJCg3NxcY90Hy9oeyTYaIMX2SHJm77d5pzMzMkI4x1is12FlZWXKycmxZeQvf8x0kK2pqXEkKzj34wAAAACga+heTzxAr1uExOmbfEB3EYlhvqORxdKObLjRKHckhBuY7cTQ4nV1dcY6NjtsoXd4v1jJnBqOrtAWCvXhmG+ARUfrwew6irXMQ+EGc/Xo0UNNTU0Rffjob1lmMpZ5M+RKwR8WellZP5EIwrbj4WkomZLaBosEk5KSYmqI5o6EMtS0L7MPZUPpOOO7/bxD1JpRWVkZdqYq774bLIN0MKWlpX7rGH91mZVzWaidIjwej3bu3Ol4J52SkhJlZ2eHNY+ePXva3omsI4mJiZa/4z0HRSozdbSFknXYy+r+aqYeDrf+6mxcLlfI2VK9SkpK2n0WTnu5o3NAJAPZI3nPp6WlJaxzjL/vhlrP+2vLhnP929k6HzQ2NqqwsDCk35ySkqLU1FRlZWW16pyTnp6uiooKv8G/qampneKaEl1LLI8k16NHD1PTeTweFRUVSTLf6TMUnaEOKysrsyWhQKjs6KTZViyNZAQAAOy3aNEizZ49W5I0ePDgsEcnQOxbuXKlJk+ebLzvLvc9ARwU+1fWsA29bhEO7z7Sdh+yGuwAdGd2DPNtVmFhYcSyWNq5jEhm33SalcDstkFK3rpVku3BM94MI2632/SwhcXFxaqsrOxwus6w7bpKWyjUh2PeAIuO1oPU/lwfaB3FWuYhMyMAdKShoUEjRoxQfX29ysvLVV1dbXMJ2/OXUdSJ9RoXF2cpC14kgrAj/ZA3MzNTaWlploPzU1NTww4SDOdBsZWHsikpKZaDXpubm0MK1LSzE4nb7dbAgQON4HOXy9UuG2VHampqtGfPHqMOk/zX92aCjHzPZeHUXeFkHrSioqIirP3Te46PlKysLMvfcblcSklJidg67cysBtKZqZtCCa7uzJxus1htLwc7B/Tp08fuIrYTjXs+Tg1ZLoVWz7edLpzrnXAyNocrKSkppO+1HcXHLG8G/bKyslbXEnv27AlYp/s7pwNOi+WR5My2uffu3Wt6nuHcuwn3mjsSamtrQ2pzxqpYG8kIAIBgCgoKNGTIEEfm/d133yk/P9+ReXdFkyZN0qpVqyQRAAwAscSesSZt4vF4VFNTo8rKStXU1NBzwEbem/ttb6J4b+4HG+oNkA4GARx22GHKz8/XgAEDlJ+fr+HDh3eq4CYgmiJ5I9s326LT7Pxd3sCvrsBKYHZLS4sGDx7crm5NT0/XwIEDbQ9oKy0tVU1NjelAxNLSUtNBe7GqK7WFvA/HzEpISNDAgQOVnp4edD1YWUexlnnIOwJAOMrLy5WamqqBAwdG5CGXv2PQyno1O21mZqal3xOJIOxIZznyFxQdie9KCjmY2exDWd/rZqv7bVxcnOPZ/oNpamqSy+VSbm6ucnNzlZOTY1xzmA1CKysrMwKUA9Vzzc3NQYMdfM9lnSFjmDdbcKjq6uoi1j51u90h16t2jy4QyyIZGJuZmRmxZXUWjY2Njh77VtrLZs4BoQZQmtWnT5+o3PNxashy77y928DsctpOF069GW7G5nDs378/Ksv1vZYwky3Z95wORIKZ68hojSTnxDkpnHs3dlxzO83Kva7MzEzb17GVgG4zz0OtdKIFAADmzJo1Sy6XSy6XS7NmzYp2cdCJLViwwNiXJk2aFO3iAOgkYubJU1fJcBaL6HULO7lcrogMXw10RZF+MFZTU9MphptvK5qZOfwNkx3KudF7s92KyspKDRgwQLW1taqqqjKWn56errS0NNXU1GjXrl22BKuUlJQ40iEqVrOqdLW2kPfhWEcZMLOzs5WUlNRqP7aS5dmftusoFjMPpaenq6Ghwe+w02Y4GRhidnlmj02Px2N63WZnZ1sql9l6vaGhQTU1NSHVlZHOxlRaWqrS0lLL15i1tbVh17uh/karmY2tljUhISHszLF2aWxsVE1NjXH+9WYctBKoU1ZWpj59+oQdeOxdH50hY5gUfiB5pLS0tKi4uFipqamW6gyPx6P6+nqHSxc7wskAZzVAo76+vsNrBY/Ho/Ly8pDL0xl5201Ws5NbYbZOMXMOcDqI3ZtVPtKc7szjbX+F2uksnOvf8vLysK81QxXt65yioiIdOHDA1LRlZWWW269AOGJ1JDmn2qORvu6NNLMdsRMSEnTYYYeptrZW+/btczSje1tmn4fG2khGbdl1HxUA0HX07NlTJ598ctDpPv74Y6PzaY8ePTRx4kRT8wYAoLOLiUBdK8N5wrpIDF0LAOhYVVVVyIFjsc7ugM9oZfqxq9OQv/mY/V7bc7bv8nv16qW8vDzLw5P749SoBbGafbArtoXS0tKUnZ2t8vLyVkEaHT1ItJLl2Z+268hMwHA0Mg/17du33XoxyxsYUltbG5HRPfxlTjRb7ubmZtNZ2erq6izt22YfCIca/CqZ23+cYPUa046H2Lt375bb7bZ8TWv1oazV4zstLS1mglD37NkTdlCct44K9zd5z2XR2ketiouLC/m7kczeKoVWZ3Sn7GBZWVkRDbwOdqzU1tZGPKtl2wBZb0ejSPF2YMjIyHAsSNlsezna9XO0hnmXDh4LxcXFjs2/qKhIbrfbdEBw2+l8O8FZVV1dbWR6jHSCikiPZtBWY2Oj6bZrVw8iRGzydpKOpaBDp9qj3nrQav0TbuffSDHbfvGe91NSUrRr1y5blm3met7K89BYG8nIF8mXAAD+5OTkaPny5UGnmzRpklatWmXpO0BXMWnSJEaXB7qxqKdeCWU4T1gT671uAaCri9aN7Eg9WLU7k1NFRUXEz/uBhsn2HaYznPmYFWz56enpGjhwYExmp4jmw/xgulpbqKqqSlu2bFFJSYlx/LndbmVnZ3c4PLEdv6/tPLz7ZNuHQgkJCRo4cGBUHs5UV1eHXC95MxlGal/Iyclp95mVB3FO7dtWhzS1WlfGArPXmHYNUR3KNa3Vh7JWH85WV1eHFeRpJzuCARMSEmw5dn23U6A6LlYkJCQY2YdD4cRwv2ZYqTM6y7nZDuFsS0mWOxsF2/bRWPcDBgxQfn6+8X+kh9f2boO0tDRH5m+lvRzteidaw7xLB9u14WSXDqa5udm4Zgt2HoyLi2u3zTwejy3Xq5FuPzm5Ts0yu09FO6gY3Zd3JLmMjIyoZRVvy4n2qLcetFr/2NEpLpZ4zwF2/q5g28nq81BvJ9qORON+nF33UQEAAACgu4l6oK6VDGcITSz3ugWAzsTj8aimpkaVlZWqqakx/XAuGjey4+LiIpYZ1O4gn6ampoie9+3qNORkQHZRUZFaWlpUU1MT8cxmZkXzYX4wXaktFOhhSEtLi0pKSowMXf7Y8fv8zSM9PV2HHXZYq8CajgKGQ61LzfB4PCosLAzpu26329iHI7UvNDQ0tPvMyoM4s/VvoOk62hahPBC2Eozq8Xi0e/du0/O2W6SvMUNZntWHslaD/BobG1VfX2/pO7EsKyvLlmO3bRa/tLQ09e/fX3369Il4Btpg0tLSwnooX19fH/FASF/B6gyPx9OtsiqG20ndynlBCl5nmB2i3k5tO0dEOljPu3yngl2stJejlbAgmp2tfPXr18/xwNJQjzm7h0aPVIIKt9sd9dFDMjIyTE0X7rZ38noDcJq//bftNbe/Dp+h2L17twoLC1VSUmLqXlOo9zZj9V6R97xv1z1bMwGzVp+HmulE69u+iET9R/IlAAAAAAhd1KMRulqGs1hkZujaWM6CBwBWeDweR4apC2c4r2icw/Ly8jr83U6tJ7vs27cvYg8Rrdwk76hMTgZkNzY2asuWLbZnL7ZDXFyc8vLyov4wvyNdpS1k9mFIWlqa3+M53IckHa0jb+ahYJweGnHv3r0hHyctLS3GcZ6cnNxu+G0n+NsnzQxvmpOTo9raWtOBn/72BzPbwnf415qaGpWWlna4HDN1pVcsdDwwU2fbGZgZambjjvYF34eyoWT/7SpBkKmpqXK73abq+2CqqqqUmZlpvG57nMSSyspK5eTkhFxfNTU1GUFThYWFEW9nNDY2qrS0VH369GlXT8X6uneClTrUH5fLpby8PNPDY9fV1XW4rGjU0aWlpa3ONW53ZPMLePc37zDYoXToyMrKUlVVVat9NyEhQbm5uZbaOmaPRzvbK4MHD46ZDJLSwWByu4NifZmpX5qbm9sdl3afO8M99s3yeDy2jRQQKpfLpaysrA63a1ZWVljHPkOxozPraP/1zfbeo0cPxcXFhd12a2lpUXl5uSSpuLhYWVlZHQaFhtopLtIBmy6Xy9QyS0pK1KNHD9s66prpkBPK81Bv3dV232jbvohU/WfXfVQAAKzYt2+flixZojfffFObNm3S3r17FRcXp759++roo4/W6aefrpkzZ3Z4L9ffeXrx4sVavHix3+mffvppzZo1q93n69ev13vvvad169Zp8+bNKioqUl1dnXr16qXc3Fwdc8wx+ulPf6ozzjgj4vc1QrFo0SLNnj1b0sH7AgUFBZIOPmt66qmn9Nprr6mgoEDV1dXq06ePxo0bpwsuuEA///nPTS/jq6++0pIlS7RmzRp98803qqqqksfjUXJysvLy8nTIIYdo7NixOvXUU/WjH/3I1Dy3bt2q559/Xu+8846+++47lZaWqkePHurXr59OOOEEnX322ZoyZUrQ+SxYsEB/+MMfJEkTJ07UypUrJUkbN27UM888o7fffluFhYUqLS1VS0uLKioqNGbMGO3YsaPVfFatWhWwLXjrrbdqwYIFxvuVK1dq8uTJxnuz7eV169bpxRdf1IoVK7R7927jPvagQYM0depUnXfeeRo5cmTQ+QRafmVlpZYsWaJ//OMf+vbbb1VeXq7MzEyNGTNGZ511li688ELTSQJ27Nihv//971qxYoU2b96syspKNTU1qWfPnsrNzdXQoUN19NFH66STTtIJJ5zQKY4VwC5RD9TtShnOYpXVB7wA0Fk5dUPSm8GyLe9wXpI6nH+kz2G9evXqsDx2rycnMhJWVlZG7NxkV6chpwNJYjFIVzo4RHGvXr2iXYwOdZW2ULgPQ/bt2xfW8sNdR+HWpf74djqIi4sLO5ijqanJqCMjEaDU0fnBX+BNXFycMjIytGfPHkt1Qtv9xsq28AZh293BMhZGTDFzfs7KylJxcXHElteW2YeyUvfu3FpfXy+Px2Oqvg/Ge2wFOk5iiTeALDEx0W+G7mB8g82idQ4sLi5WWVlZq3ZoZ1j3Tgn3OE5PT1dtba0RdOPksiIh0sHC3nq6qqoq5CDdfv36KScnR2VlZWpsbFRCQkJIgYd2XUO63W5lZmYG7WwjHawHYqU9HEv1QNtjxYmAs0gcj7HQSaq5uTloALbVEQJ8OXG9AURKsP23bfCpEw+yy8rK5PF4lJeX5/fv3uz9sXp/yis5Odn0eXzPnj0aPnx42J39JBkBJx0lRDB7fm9sbDSub6TWnWj9JV2IZP1H8iUAQKQ999xzmjdvnvbu3dvubzU1Ndq+fbteeukl3XbbbXr88cf1k5/8xJFyfP/995o4caK+++47v3+vqKhQRUWFNm/erEWLFmnUqFF66aWXNGLECEfK46QXX3xRl156qaqqqlp9vnv3br366qt69dVXddppp+mll15Sz549A86nublZ8+bN08MPP+z3erSqqkpVVVXavHmz3njjDd16661aunSpTj311IDzrKmp0fXXX6+nnnqqXXtj//79qqqq0tdff62FCxdq6tSpWrJkiaURKZqbm/X73/9e//u//xv1a2iv0tJSzZ07V6+//nq7vxUXF6u4uFiffPKJ7rnnHl188cX685//rB49elhaxsqVK3X++ee3GwWxqKhIy5cv1/Lly/Xoo49q6dKl6tOnT4fzuuuuu3Tbbbdp//797f62b98+7du3T1u3btVbb72lu+66Sw8//LCuvPJKS+UFOrOoR792lQxnsc7KA14A6IycuiEZbgZL7zwiKSkpKeDfOsuDK3+Zi5xiV6ehWO9UZDajiFWdpY3WFdpCZh9y1NTUtHso5PF4VFlZGdJy7VhHdtSlbVVVVdmeAXL//v0qKSmxbX4diYuL83v8dBSY0tzcHFIwsm/9FOq26GodLCN9jRnO8oI9lPUKZd336NHDsfNDJPm2GwLV92a53W5Tx0msqK6uDilIVzpYD8VCMJxvOzQtLa3TrHsn2FGHpqWlmQrUDbas1NRUU8GdXUlycrJaWlpUWFgY0verq6uVnJzcrv5pG4xuhpn7pWaCpaw8VIqVgJpYq4Pj4uJUU1NjdAxzIpg5Eu0nuzpJhdNuiIuLa/fQry2r1wReTlxvAJFiZv9te9x56/dAHTwzMzNDurYtLy+X2+1WTk5Ou2PFm3G+urra8nwjweVyacCAAaqpqTFd5zU1Namuri7szn7SwXaAd90ESohgdgSQtp3ZOhoZLdL1X1e7N4CDYn30PQDd17333qvf/OY3rT7Lzs7W8OHD1dzcrM2bNxvBpN9++62mTZumZ555RmeddVa7eZ188smSDmZK9V735+Xl6fDDD/e77P79+7d6X1VV1SpINykpScOGDVNmZqYSEhJUWlqqr7/+WgcOHJAkffnllxo/frw+/vhjHXbYYSGugch74YUXdM4550g6eD4fNWqUsrKytHfvXn355ZdGu3Tp0qW6+OKL9dxzzwWc1+WXX64nnnii1WdDhgzRwIEDlZiYqH379mnHjh0qKioy/t7RfYzi4mKdcsop+vzzz43P3G63fvCDHygnJ0f19fXatGmTampqJEnvvPOOjj32WK1evVoDBgww9ft//etf68EHH5R0cLS9UaNGKSMjQ0VFRfr6668lHcy8W1xcrG3btunbb7+VJPXu3Vvjxo3zO89hw4aZWrY/u3bt0pQpU/TNN98Yn7ndbo0aNUp9+vTRnj17jHI1Nzfr8ccf11dffaU333zTdJKlNWvW6OSTT9aBAwfkcrk0YsQI5eTkqLKyUhs2bDDuPX388cf62c9+ptWrVwfsOHjnnXfqlltuafVZ//79lZ+fr549e6qmpkaFhYXauXOn8fdYCYgGIiXqV0pdJcNZZ2D2AS+ArqO73GBx8oakHcN5RTrTRKBAIKfWU0pKiiMP8SP1oNiuTkN2DLftpKysLEe2U7Bhk2NJZ28LmX3IUVpaqsrKylYPhWpra0O62M3JyfE7JLlVdg+N6FRgmZnAJic5EZjStv4KdVvY3cHSqXOHWWavMe0acjvca1pvZuOOhHIe8r0J2tnV1NQY68hffV9bW2sqWCE1NdXUcRIrwhnGvKmpyW82kmgpKipSXFxcp1n3dgvUgcMqu+rrcLJadlYlJSUqKysL+QFBY2OjbZ0izdwvTU9Pt7XtEisBNaHWwVazPJqdfvfu3Y7WS50tQUVaWlq7rEpmeIfHdGq4dIZiR2cWTtvT7XZr4MCBRmBqamqqUaeEek4rLS1VRUWF8vLyWp23PB6PEfQQizwej+rq6joc8tqfpqYm2+8LBTr3WxkBxDuPuro6VVVVBRwZLdL1H8mXuh6nRikEgHC9/fbbuummm4z3eXl5euihh3TGGWcYQYIHDhzQkiVLdN1116m6ulqNjY2aNWuWRo8erZEjR7aa3/LlyyVJs2bN0uLFiyVJU6dO1aJFi0yXKS8vT3PmzNH06dN11FFHtbuOrqur03PPPaf58+ertLRU1dXVOvfcc/Xpp5+GsgoirrS0VLNnz1ZcXJzmz5+v66+/XhkZGcbft23bpvPPP18fffSRJOn555/XVVddpeOPP77dvL744otWQboXXXSRbrvtNg0aNKjdtEVFRVq2bJmeeuqpgO2ypqYm/eIXvzCCdHv06KFbbrlFV1xxhTIzM43pGhsbtWTJEs2bN0/V1dX67rvvdN5552nFihVBR6X47LPPtGrVKiUlJen222/XFVdc0ar9tGPHDqWkpBj7z4IFC/SHP/xBknTEEUcY+5hdWlpadO6557YK0p01a5buuusu9evXz/hs27Zt+tWvfqVly5ZJkj744ANdffXVRjmDmTFjhg4cOKDLLrtMt956a6t5FxUVae7cuVq6dKkkae3atXr++ed13nnntZtPSUmJbrvtNuP9qaeeqvvuu89vVumKigq99dZbWrJkiSOjhQCxLCb2+PT0dA0cOLDdiSwhIUEDBw7kQsBG3ge8GRkZSk1N7TSBKQCsq6qq0pYtW1RQUKBdu3apoKBAW7ZsCemBSqyzckPSKjuG8/IdVjgSAj1Ud3I9OSFSD4pdLlfQtoaZ4GXvzfbuprMF03TmtpD3YYgZ3gc63jo/1GAHO4J0JRm9yO2YzuPxBM3EFapIdqzwZgD15URwYNv6K9Tzmpk6rjN0sLR6jRlOEKR0cL1F6po2lPOQx+Pp9Nl0A2lb35t9YN/S0hKzWcL8CSfjQEtLS0ydxxsbG2M6+MNpGRkZttShdtXX4dZ/nVFJSYmjWTwKCwtN17kej0dxcXHKysoyAhy9vOeytLQ0S/PqiPfvsXBOCKVe6t27t+nsOF6+D/LsLo8VVtpP3iC5yspK1dTUWNpedgWn+hu60ozm5mbTHe1CWecMxY7OLJz90htkmpubq9zc3Fb3OcJpV3iPWd/7yKF2AI6ksrIy0/cfvMxk+w5VUVFRu7o60PPQQMrKytrtI773fCJd/3WVewM4yNsRvqN9DACiobm5WZdeeqlxHu3bt6/WrFmjn//8562C+hITE3XxxRfrrbfeUs+ePSVJ9fX1uuKKK2wv06GHHqqCggLdfvvtGjdunN9zeXJysubOnau1a9ca1+yfffaZ3nnnHdvL44Ta2lo1NDTo2Wef1e23394qSFc6mBl22bJlys7ONj576qmn/M7r3//+t/H6+OOP16JFi/wG6UoH2w6zZ8/WmjVrNG3aNL/T/OlPf9IHH3wgSerVq5dWrVqlm2++ud21fUJCgubMmaNVq1YZz8tXr16tf/7znx3/eEn79u2T2+3W66+/rhtuuKHddfTgwYOVkJAQdD52eeqpp7RmzRrj/a9//Ws9/fTT7dpiw4YN0xtvvKEzzzzT+Ozvf/+7VqxYYWo5paWluueee/Too4+2m3dubq5eeeWVVsG2gbb5W2+9ZbTFhwwZoldffdVvkK508D7OzJkztXTpUl122WWmygl0FaYDdUO9CWhWenq6DjvsMOXn52vAgAHKz8/X8OHDCdIFgBB0txssTt6QtGM4r0hnJgqUVSnU9RTsYaATARWRzLzg8XiCHhPV1dWm2j9Wb7ZHklPrM1Z+azgPrTuLUILwvA+FQtlOdqxD3+1iRn19fdBpampqYv7hoFltO3I4EThQVlbWqo6zel7z3YZxcXF+67j4+HjLwaiRzjafmZkZ0jVmuA8XPR6P6SGm7OA9D3XHh6Jtz3Ntzwtmb6KWlpZGPbu2Fd1xW3dVdtYVdnSIJ5jNfv466fhTVVWlr7/+WgUFBSorK1Nzc7Pcbne7c5nZTlzeeQQrW6x07g2l3VpRUaFdu3YFDUj2zt87zGY0We085LtfeDtjf/3116a3V0pKiqn1E0w4mW7MtuFD2QcYih2dWbj7pb9zdm1trS3XXL6Bpp2lbVBRUWF6nXrrRafuMQRKiOB9HpqTkxPW/IuKiiJa/3mvsTwej7Kzs0m+1MmZHX2vK95jBRD7XnvtNe3YscN4/8ADD2jo0KEBpx8/fnyr7LurV682Mq/aJSkpyfT9xeHDh+vqq6823r/yyiu2lsVJ5557rs4+++yAf+/du7fmzp1rvPcNJPXl21FzwoQJppfv77p1//79euCBB4z39913n8aNG9fhfMaMGdNqn/jrX/9qavlz587VySefbLK0zvrzn/9svB45cqTuvvvugNO63W4tXLhQWVlZxmcPPvigqeUcf/zxuvHGGwP+PTExUddee63xft26dX6vNXy3+bhx40zfd7HjXgXQmZi+MisoKPi/Lzk05IWZ4TwBAB0ze4PFTIbQzsJsRpdQbkjaMZxXJHvXSYGzX4Vy49bM0FdOZAyO5P7pxBBxsRhE6H1wbWdwXKwMZdedhmjz/p62vzcQ777rfTBvZfu3tLSENTSiv+0SjJnjPlayftuh7bpxKnDA97xv5bzmbxv6C84I5aFNpIMk0tLSQtqXMzIyws6uWlpaqr59+4Y1DyvS09Pldrtb3czubvztu3FxcbafB2OB1YxhXnFxcUpJSVFpaanNJQpPSkqKKisrO00giJ3s3jfT09OVlpZmtHXj4+OVkpJiuo0dS8Fsbrdbbre7S+wXNTU1HZ6PvJ1u22ppaVF5eXmrbWhl+GyzAg3VHUlm2ir+mDmGsrOz1bdvX7lcLpWUlIRaxLDl5ORYGrki0H7hm6U22PZyuVzKyMhQWVmZ9QL7SE5OdjTjdqjXmAzFjs4s1HrPy985265zpu/9sFhqGwRj9vfn5eU5PqJDoLK4XK6w7xk3NjYanbOdrv8CXWNlZ2crKSnJclsT0efEPXEAsItvYGv//v01c+bMoN/55S9/qbvuust4ZvzKK6/oyCOPdKyMwRx77LHG648//jhq5bDqqquuCjrNxIkTjaDRbdu26cCBA+2CMr0ZjiWFHTS9bNkyFRcXS5KysrI0e/ZsU9+76KKL9Pvf/17SweDSurq6gKPSel1++eVhldUuW7du1aZNm4z3v/rVr4K2x3v37q05c+boj3/8o6SD662hoUE9evTo8HtXXnll0PJMnDjReF1fX6/t27fr0EMPbTWN7zbfsGGDmpubCcIF/AipC3xXzcjYHbS0tKikpESFhYWOD+kHIDqs3GDpCjwej6msZ96bhVbZMZyXleHq7RDoAaWVYVYl85mZnchEVFFREbHe+nZmZPaus1g8vzY3N9seABILQ9l1twzi0v9lXunTp4+p6b1DYfbu3dvysvbt22f5O1Lg7RJMsIdUHo8n5KC0WNT296akpISVpSwQ3/O+2fNadXW1323Y0tLSro7zNyxqMMFuiNkpLi5OTU1NIWXbtuNhlJlM0cFYzRre1YJRzfD+5srKSr/7rhPnwc4sFrMiJSQkKDU11XL2+K6isLDQ9u3i7RCfkZHRaihsMyJ9DdORUEYV6Iw8Hk/Qobfb7ife7Ml2P/iIZvY07xDuoYqLi2u378bFxSkzM7PVPYFoPixKSkoyPa2Z/WL37t1Bt5eZkWTMcPpcGuo1ppl6IicnR7W1tV16FBZ0TuGc57ydr9qy8xzubVdH8houEpKTk5Wenu5IAgJfTo/C1tzcHNK9ayvXmIHu8TQ3N6ukpMRoc0b7HiGscXKUQgAI17p164zXp556qql75r1799YJJ5xgvP/www8dKZskNTQ06I033tDtt9+uWbNmacaMGTrllFM0bdo0499tt91mTL9r1y7HymKnhIQEjR07Nuh0AwYMMF4HutY85phjjNdvv/22rrnmmpA7zK5atcp4PXHiRNOdnQYNGqSMjAxJB89n//3vfzucPi0tTWPGjAmpjHbzPQYkafr06aa+d8YZZxivGxsb9cknnwT9zvHHHx90Gt9tLsnvKJq+23zz5s0677zzunUyESCQsK4Cu1pGxq5uz5497bImFBcXKysrq1s88AC6i+52g8XsUG69e/cO63zldrvbBSbFxcUpLy/PVOYauzMddSRQzzizAXfNzc2WMjM78YCzpaVFNTU1ERku3K4h4jwejwoLC+0okqPi4uLkcrnCqgPcbrcyMjIUFxcnj8cTtbZgd8wg7uV9CGImE2I4D35qamrU0tIS9EaYx+MxOorExcUF3S6B+A7L01ZVVZUKCwu7VKCdd9v4rr/MzExHMlz6HvPe89auXbv8Poyrra0NKYusleMtkh2GmpubjZuhVrNt25ExLtw2l9Ws4VVVVUEDerqiuLg4FRYWBu3A5W23dKW6JBTetlYs8QYQWM0e31U0Nzc7mq3K91zjL+OZv7/n5ubGxMOk5uZmud1uZWdnq7y8POaOX7fbrd69e5vKVNpR51Fvu6sjzc3Nfq+T7G7rRjt7mtlRc/xpbm7WoEGDtH//ftXW1qqurk7Nzc0qLy9XeXm5cQ4NN2N+OHbu3Gm6TWJmvzBz/WymU7cZFRUVYc/Dn4SEBOXm5oaVyTnQ+SMhIUFpaWkqKirqFqOwoHOyu/0TbpZeX97rViezaUeDt9OEEwkIvIJlsk1OTg571I/4+HjjfO2v/vNXt1q5xmxpaQl6v7Or3nvr6uy6Jw4AdmtqatJ3331nvP/hD39o+rtHHHGE3n33XUkHM73arba2Vrfffrv+9re/Wbqm9BfUGIuysrJMBcG2bd/4ayfOmDFDhxxyiL799ltJ0l/+8hc98sgjOuGEEzR58mSNHz9e48ePN/UceMOGDcbr9evXa9q0aUG/49XQ0GC8DhYoPGTIkJhpz2zdutV43adPH+Xl5Zn63hFHHNHq/bZt21oFsPtjprO0mW1+7LHHasKECfrggw8kSf/4xz/04osvaty4cZoyZYqOPfZYHXvssR0+BwS6g7Ba19G+aQvz/AXpenk/J1gX6Bq62w0WszecrWSs8RVoiEnJfICH9+ZnpPgrV1VVlanMw9LBfcNKZman9qWKioqIBOqmpKQEvSkeKEOJL7NB49HW3NyswYMHG8G6cXFxlrMAe4fe9X3QHY2Hm919iDYz9Z/vQ6FQAh7279+vr776qsOOXf4e8IQiKysrYEBwR3VxZ+btbd52/blcLtszfLWtq+vq6gIuw+z5oi2zx1tVVVXUAr+sDultx4Pt+vp6VVVVhVRPBtr3A/2OrnqsmFFRUWHqBnlnOFdHih3Znp2Snp6utLQ0ff/991ENpou0mpoaR9oswYIxAv09lGz8Ttm1a1fMHr8tLS2qrKz027nTV1xcXIfb12wnlvLycuM6ycl6P1qB8lVVVSFn2fHavXt3wP3Few6N9j0Rs20Ss4Gxwa6fY7Xjg9vtVlZWlvr27WvLA1Hv+cO344F39Ie2rLYLAaf57r/79u0z1QEkUEcfu5IG+N5TiNV6JFTehAZmO0GHoqMs4d72VzjtG9/t46/+a9sxy7tcs3WitxNosHuGXfneW1dmJqA/WLA5ADihbVBrdna26e/6Tmt3J8PS0lKdeOKJ+uKLLyx/t7OMEhjqs3R/zxmSkpL05ptvavr06frmm28kHWxvrFixQitWrJB08D7J2LFjddZZZ2n27NlG9tu2fNvFO3fu1M6dO0MqZ7BRZtLS0kKarxN8918rx0CvXr2UlJRkPA80cxyEst0DPVt6+eWXdcYZZ+ijjz4ypvvoo4+M9y6XS0cccYR+8YtfaM6cOaYDkIGuJOxxVbvaxXlX1NLSEvSmTllZWUwO0w3AOjNDlHalGyxOBiabzdYZytBgTqqqqmp1sWHmd3h59w0rmZmdGjI0ksNQmh0mtKOh4DpTm6i5ubnVMMiZmZkhz8t7Iz8aPYK7WwZxXx6PR0VFRUGn8z4U8ng8prNq+1NWVua3HrGzjgs0jKaZ4X47q3379vldf956pm3gstvtVmZmpuVzWtvzvpnrg1AF2xe8+0y0hxo2O6S3Xee4UIa0t9oOsXK+74q6UzCnr3CCmmIlQ4RX2+PS5XI5muGsuwh0rva24fbs2RPw7+EGS9opVoN0vZqbm4PeV8vLy7PluNu3b5+qqqocr/cbGxs7PHdZGTLbLLt+k5n9JVauEYK1Sczerw02XbQDkwNpaWlRSUlJ0AemVnhHH8nIyFBKSkrY93WASPLuv/369TN9ryZQHZyWlqbs7Oywrml8A02duv8XLU1NTWpublZKSoqp4bStSEhI0MCBAwN2AjBzLyUhISFotrG2gcC+9V9qamq7doeVa0xvGc2eh2LlvArzvAH9Heko2BwAnNI24YiVe0O+AYe+mVTtcMkll7QK0p00aZIee+wxrV+/XsXFxaqrq1NLS4s8Ho88Ho8RjNqdDR8+XBs2bNBDDz2kI488st3fm5ub9Z///EfXXXed8vPz9cQTT/idj12j8wVr19jdJgyH73Fg9f6ok8dBMDk5OVq7dq2WLFmiCRMmtFunHo9HX3zxhX73u9/pkEMO0Z133sn1OLqdsO/QxepNPvwfsw/hy8rKLPXGABCbzGRM6Eo3WJzs+R1uts5oBsz4DjlmZYhL775h9vy+f/9+xy5cAgXt2a22ttbUUKLBhk3vTG0ib1ntyoQqHcxy5jtcdSR0twzivswe194HaXYMb15WVqacnBzjmLe7jgs0VKKZ4X47q2AB7m1vUHizWbddR8Ey8LY97zsVpCt1/PA2lgJJzWb8sau9FGio8o5YbYeEMqS1E9mbEVmZmZkhH9Oxdn4kE1f7YeTCZabedfKc0B0FyqqblZUVtJ2ckpJiOqNfUVGR4uLiHA2KKS4uVllZmd9rHytDZlsRyrmsswtW95kZdtTMdGbunUSTU9eT3X0UFnRuaWlppkY7KS0tVWVlZas62I77PW0DTf0Nb9vZ7dy5U0OGDFFmZqYtWXXT0tKUmZnpN5Otl5n2WVxcnA499FC53W4lJye325YJCQnKzc21XGearRNramosX7vH2rUFzPHuQ3btYwBgh7ZZVa0kIPHtyB8oO2soNm3apNdee814f9ddd2n+/PkdfiecxCldSVJSkq666ipdddVVKi4u1po1a/Thhx9q1apV+vzzz41701VVVbrkkkvU3Nysyy67rNU8fLfllVdeqYcffjiSPyEqfH+zlX3J26na33wiJS4uTueff77OP/98VVZWGtt89erV+uijj4zO1Q0NDbrllltUU1Oju+++O+LlBKIlrMgaf4FPTmRTQHgaGxttnQ5A7EtPT9fAgQPb3SAL1pu/M3Ky53e42Tqj+ZCxsbHRuFFvNkDP9+GxmczMklRSUmJLAGCg8kSC1W3kzT7WNuNPZ8pSnZKS4ki2Z3/rxUndLYO4L7Pbrby8XB6Px7ZhnnyDeeyu47wPyNuyq7d0LAoWgBzoWqrt58Guudo+UHWy3V9fXx/wb7EWfGOmLHaW1+q+bLUdEkpZc3NzYypTAKwLJ5g8FjtB+O7HVVVVjg1DHIvcbrftQWKxVu92B4GOq7KyMlvbyd4gGqf5u/YJlqXZ7O/0dw+5u+6vHf1usx1Yg01n5t5JtDlxPdmdR2GBdbHwbMu3DB6Px3Two28dbNf9nradMCOdjSsSamtrba13EhMT/WaybbvMYNumubnZuI5PT0/XYYcdpvz8fA0YMED5+fkaPnx4SPf3ze4TVtuQXfXeW3dh5z4GAHZISUlpdX3z7bffmv6u77R9+/a1rUzLly83Xufn5+umm24K+p2OEmp1Vzk5OfrFL36h+++/X59++ql27dqlBQsWqEePHsY0N910U7tnDLm5ucbr4uLiiJU3mnz33++//14HDhww9b3vvvuu1b0pO4+DUGRkZGj69Om6++67tXbtWu3du1cPPvigevfubUxz3333cbygWwmri2PbwCensikgPHZlXgDQuaSnpystLc24sRYfH99hb/7OzKme3+Fm64z2gx6rFyu+Wf7MZGb2ciKILisrK2KBQ6FmfPCX/TNQBq1Y09TU5FhWy0BZUZ3Q3TKI+zK731ZXV2vLli22ZTbxDfB0oo6Ldr3ZVbXNhuxku7+jbRhr29fMcRHN4V2ttkNCOc4TExPpXNuNxWKbxbsfx1IG7kjJysqyvc0Sa/VudxesnezNKBKLvGWXZGrI7GDXA4HuIfs+qLEqLi7O8jrMzs5WSUlJyMu0S0ftDTvv66anp6uuri6mM2kXFhbaej3ZnUdhgTWx8GzLXxms3hvbs2ePbe37tu2IrnhvRTp43ork88tQOhC4XC5bOnQ5Vdd11Xtv3Yld+xgA2OXoo4/WmjVrJEkffvih6e/5TvujH/3I7zS+7Suz7aYdO3a0mq+Z894HH3xgat7dWV5enm699Vb1799fl1xyiaSDoxD+5z//0eTJk43pjjvuOL3xxhuSpP/85z9RKas/oexLZh199NHG68bGRq1fv17HHXdc0O+1PV4CHQfRkpmZqWuuuUajRo3S1KlTJR1s97777ruaPXt2lEsHREZIETD+MjIGy6YQbFhXOMdsRsJIZS4EEDneGywZGRlBe/N3dk70/A43W2dnetDj3Te6UrBOS0uLSkpKVFhYqJKSkoDBKKH+5rbZP2tra2My4MWfHTt2OBa40Xa9OJ2RpjtlEPeVnJxs+oFdU1OTbZlvfLefE1lZ/dWbPCiwh29AhpPt/o6O8Vg6L5rN+GNn28lq0K/VdojV+tVbnq507u+OwgnsM5uJIVJ89+fumAnWN3uIFf7avN7PIjnSAYILNHqAl9Xz5P79+8M+t8bHx5tqL3vLbnbI7I5+Z0f3kEtKSkLqJJOamqqBAwda/t7+/fstf8cJHbU3rLQHgl17VVVVRSRINz4+XgMHDvR7nRZMc3Oz9u7da+k7Hf3u7jwKC8yzK1O4E2Xw3mcyWzc2NTXZ1vGj7TV/z549bZmv06yeRxobG21LFmCmfR1qBwI77q+ZrRO5DwMAiLZJkyYZr99//33t3r076HfWrl3bKqOu7zx8+Z7nOhodzpfVZyFlZWV67bXXLH2nOzvzzDNbvS8qKmr1/pRTTjFe7969u1WG42gKZV8y65hjjmnV/l6yZImp7y1evNh4PXjwYOXn59taLruceOKJre5Htd3mQFdm+k5Zfn5+wIyMZjKd7Nq1Sy6Xq8sGS8Syffv2yeVydXjhHsnMhQDgFLt7foebrdN787MzBBl4PB4VFBQY2ULS0tKimsWsbfZHq/bs2dPuAWRxcbGysrLaDfcZTrCh77btDNvZy+nAHO+6iFRGmu6UQVz6v/UajcBw3yAiJzKN+gtSSklJCSlDmhXeh/NduXOhb13ncrmCXh+EqqOHt7F0XjSb8cfOsloNVLHaDrF6jDQ3N2vnzp2WvmOHzMxMpaWl6cCBAyosLLRtvk7t07HOG6gXyr4aa+vLd392ojNIrAtlVIJAbV7Ero72bavnyX379mnAgAHatWuX5XJ46+KUlBRjmPRgrNQzgab1eDy21v1eAwYMUFxcnOX6sLq62vayhKKjMpttD1RXV3d47RXJTOXe84v3Oq2mpka7du0y3VYpLy9X3759TdWHwa45u/MoLDDHzLHh9MhBZsrgcrnUp08flZaWOlIGf9pev0RztBEr+vXrp927d1tq68bHx9sySlZtba08Ho+pDhgd1f1tOxDYdX/NbJ1otU0SydG1AADdw8UXX6y77rpLzc3Nam5u1o033qhnn3024PTNzc264YYbjPe9e/fWWWed5Xda32eE33zzjany5OXlGa/XrVtnPIcKZN68ebYHbnY2wdpEvmpqalq9z8zMbPV+zJgxOvHEE/Xuu+9Kkq699lp99NFHUY89892Xvv32W7W0tNgWc5WSkqJzzz1XTz75pCTpySef1NVXX61Ro0YF/M6yZcuMdSRJl112mS1lMcvKNt+/f3+re2RttznQlZmuJTrKyGg200mkeh/j/3h7YgcL0m0btAQAOCicbJ3em5+diTdbyN69e6MeSBVqph9/AQu+82z78COci2Xfi4hYyhQZjNMBno2NjRHPSNNdMogHWq+R4rvvOBE46y+4yOVytboR5oTGxsYuHaQrtR4O2fvw0AmJiYkB/9YZz4t21u2hdJLwtkPaPhT3ZqrzbYeEUtZoBGp6b1baHUwYajbSzq6uri6sTKyxwF+7Otrt0GgIloW0rY7avIhdwQIyrR7PjY2NGjhwoOUHQb169ZIkVVRUmG4DxcfHh5wF0Gvv3r1B25DNzc2t2i1mNDQ0dOoEEcGyJlZUVHT4/ZKSkqAj3ZWWlkasbm1ubjau+Vwul3r16mWpPd/c3GzUhx1lkAx2zbl7926VlJTI4/EoOzu7243CAnPsyBTuK5Ssp2bKYGemXLPa1sWRXn6oqqurLV/nVFRU2NI29q2/AjFzXezbgcDu+2tm7nVbvXa32o6NBKdH+AIAOGvw4MGaNWuW8f65557T7373O7/n6/3792v27Nlat26d8dmNN96o5ORkv/M++uijjdcbNmzQW2+9FbQ8P/nJT4zXu3fv1i233OJ3uqamJv361782nf20K5s5c6Zuu+22oJ11m5qadOONNxrve/TooWOPPbbddH/84x+NeyZbtmzRxIkT9fXXXwctx44dO3TzzTfr+uuvt/gLgvPdl8rLy/XEE0/YOv8bb7zRSIzS2Nio0047TVu3bvU77bp163TOOecY73Nzc3X55ZfbWp5grrnmGl1//fXatm1b0GlvueUW1dXVGe8nT57sZNGAmGLLU0crN/noWRk5Znpix8XFKTc3N0IlAoDOKZxsnd4HPm2zHsS68vLyaBchpExqLS0tQQMW2mbrDadN4ntTO9BFf3dkJviKNqF1kcyCFYhvsKDVAAozAgUydta6NJb49kh2ch0Gqwu927KjDD6RYLYOSkpKsm2ZFRUVprPDtWXmO7GUsbgjpaWltmcCc7lc3TpLRdusE2ZF6hycmJiovLw8ox2dnJysurq6DtvVTpxjOgOzx6+ZNi9iU0eBri0tLZaP58bGRjU1NVkOLtq9e7fl80VycrJcLpflLIBeHo/HdP1v9fc0NTXJ4/FYClaKlUzsZrImBtPQ0NDh30PJumwH3/ZWenq6qaBjr6ampg4zSJoZBajtsuLi4pSdna2kpKQuPwoLzDN7rJmZLtSsp2bLYPb4sUvbcnWWDuqhZEu381rCzPYMdI8jISFBubm5xt/N3AcqLCy0fH/NzL1ubxl2795t6rwcS9ehkRrhCwDgrAceeECrVq0ygv7uuOMOLVu2TLNmzdKIESPU3NysL774Qk888USrzLg//vGPW2XXbesnP/mJ+vfvb2TgnzZtmkaMGKH8/PxWSSh+9atfGQG6EyZM0Lhx4/Txxx9Lku655x599NFHuuiiizR06FDV19friy++0NNPP20Ej15++eV69NFHbV8vnUVxcbFefPFFLViwQMcdd5wmTJigH/7wh8rOzlbPnj1VUVGhL774QkuWLNGWLVuM71133XVKS0trN78xY8boySef1AUXXKCWlhZ98cUXGjVqlE4//XRNnTpVw4YNU69evbRv3z4VFxfriy++0OrVq/Xpp59Kki666CLbf+Pw4cN1zDHH6KOPPpJ0MIPtPffco+HDh7d6rjBz5kzNnDkzpPnff//9uuKKKyQdDDr+4Q9/qNmzZ+vEE09UVlaWioqK9MYbb+i5554zOtbFxcVp0aJF6t27tw2/0rzq6motXrxY999/v4488khNmjRJY8aMMUZs2Ldvn7788ku98MILWr9+vfG9c889V8OHD49oWYFosuXK2soFurdnpZ1Dk8M/Mz2xvT182R4A0DFvts5Q+N78LC0tDTmYIpKsZMlIT093JGN+KAEaZgMWysrKlJ2dHfJyvHy/69vzD8HRJrTO7CgWTvJ9eOXEQ7qOsrF669LS0lKG9Q5BfX29cbw5+YC1rq4u6HFtNVDDCWbroN27d9u2zKamJsv1njd7kr95eT/3Pmg0M4xpV5WYmKj9+/dHuxidjtvtjkhmtJSUlHb7fbDjoLMEgtjN7O8mSLfz6qgtF8p2bWhoCOk6JJQ2pfccb2bIbH/BQlYy+lutm+Lj4y23lXv27BkT13D+siZ2FW3bW+np6abbf/v371dJSUm7z71toOzsbMv7cXNzs0pKSjRw4ECuQ2EIN1O4l5V2e6hliLRdu3a1ylYe7fsRnYXZ7WkmWNbsM769e/cqJyfHUjnN3OtOT09XXFycCgoKgs4vVvbjcI5FAEBs6dWrl1atWqVp06Zp48aNkqRPP/3UCLz0Z+rUqXrllVfajU7mKz4+XosXL9YZZ5xhZITfvHmzNm/e3Gq6n/3sZ63eP/vsszruuOOM65SVK1dq5cqV7ebvcrl06623auLEid06UNfL4/Fo7dq1Wrt2bdBpL7jgAv3hD38I+Pdzzz1XGRkZOu+881RZWamWlhb961//0r/+9S87i2zJwoULNWXKFGO/2L59u7Zv395qmjFjxoQ8/8svv1z79+/XvHnz5PF4VF9fr0ceeUSPPPKI3+l79Oih559/XieffHLIy7TD559/rs8//zzodFOnTtVjjz0WgRIBscPauGgBeDP3mMUFfWTY2RscABAel8ullJSUoJluOhu32+3YA65QevqZHVbcd7pQexS2zXzE+dQ61pk1sba+rF4DmBHswZLL5VKfPn1i5gFQZ+K7/ziZAdzsfmp1aG8nmCmr2fOKncv0MpM9qaioqFXQU6BhTLs6u7dTd+EdOs1pVoMGpO45UkGgLKT+hDLyBGJDR/VzKNs1koGm3nOYmSGzO/q+3bzHjtX5R7uDR9v1FQujZzjBd7ukpKQYI9sEEyygN5xRgNq2n9C9mW1zdDRdKO12X05cW9vFt9xmj9/uzHv/18r0qampysjIUGpqaruOLmbPbeXl5Y7Va2b2TyvtWCeFeywCAGJPXl6ePv74Y919993q27dvwOmGDBmihQsXatmyZaaeWU6ZMkWbNm3S/Pnzdeyxx6pPnz5Bk/oMGzZM69ev16mnnhpwmsMPP1xLly7VrbfeGrQMXd1NN92kCy64QP369Qs67dixY/XPf/5Tf//734O2O0499VRt3bpV8+fP73CfkA6OlveTn/xEDz/8sO6//35L5Tfr8MMP15dffqk77rhDEydOVE5Ojq2j9EnSNddco08++UQnnXRSwDZ5YmKizj77bG3atKldkHmkXHbZZbr00ks1ZMiQoNOOHDlSCxcu1PLly+lIi27H5bHpisRKj//8/HwOthB4PB5Lw67X1NSY6unau3dv9evXjxstQBdhta5AZLS0tGjPnj1RzR7olJycHEeyW+bk5BhZb83avXu3qXXcu3dv9e/fX5JUUlISUvnbPoQOdT7dWTTahMHqyFipQ/2Vo7a21lTbzkm+x44U/BogLy9P9fX1qq+vN9VRIdg+4V0v+/btI5ugRb7r1ux1QrjL6YjZ+tpJZsq6bds2WzvZWKn3zG4nf/Nsbm5WUVGRDhw4oAMHDhDUB7969OgRkU5kgwYNktvtNs5pPXv2VHl5uRobG5WQkKCsrKx29yOcrKdiVUcBjm3R7uy8OjoPWN2uCQkJEa3f25bdX3tVUsC2tFPHtffYCWX+aWlpIQ2RHq7U1FQNHDiwVZanrlrvtd1viouL/WbKjTSeT8DL7LE3ePBguVyusOq3jva7WM6o7S13LFzDxbqUlBRTgQlmWTk3OFmvBds/rbRjnWTHsQgAiF0ej0fr16/Xpk2bVFJSIrfbrb59++qoo47S6NGjI1qWgoICrV69Wnv27FF8fLz69eunMWPGaOTIkREtR2exc+dOffnll9qxY4cqKyvV3NysXr16afDgwTrqqKM0cODAkObr8Xi0ceNGbdiwwRjRNiUlRdnZ2TrssMM0evToiCUqiJSysjKtWrVKhYWFqq6uVu/evTVo0CBNnDgxpto3xcXF2rBhgwoKCoz7wKmpqerfv7+OPPJIDRs2LNpFBKLGtm666enp8ng82rVrV4fTxUrPys6mqqpKe/bsadWD1nvSD3QB7O3pGqzXbUVFhSoqKpSVlWWqRwuA2BVKXQHn7dmzp9MFlMXFxZkebjQ+Pt7U+caqUB46Jycnm3po4JsJxepyEhISlJub2+6YitXsJ7EqGm3CYHVkrNShgcqRm5tr6lhre/xaOZ6DaXtTw7te2pY3ISFBSUlJKiwstDT/jn6bv/USbVbrPpfL1WHmlmB/D1XbrD5OZ7TrDMyWNTMz0/J+HO4yvUpLS01N13Z7dsZ2B6IjUp11d+7c2eHfi4uL292P6IpZJTuSlZVlqa2RlZVFoG4nFOw8YHW7RrLDvb+ytx0yu6O2tCTbzqe+evToYRw7Zu+D+kpLS1NLS4tqamra/c2pdpl0MJBo8+bNreq+WGrj2sXffmN3ZqFQdcX1jdCY3Rd27drV6rra916BHSMbeuuy3bt3q6WlxdT8IsVbbhJBBJeRkWHr/LyZyM3sE07Wax3tnx0NLR5pjDIKAF2by+XS2LFjNXbs2GgXRfn5+crPz492MTqNQYMGadCgQbbP1+Vy6YgjjtARRxxh+7xjVVZWlmbMmBHtYgSVk5OjqVOnRrsYQEyyNaIkIyNDLperw56Vubm5XNBbFKi3alNTk/G5vwc6LpdL/fr1M90T2/swl2BdoHMKta6AszprsExKSorpzEIJCQnq0aOH34eb4Qg2zEw43/Gdzux30tLSlJmZGTDDaijl7c7S0tIi2iYMVkfW1dX5PVYjXYd2VM5du3YpKysraJ3S3Nys7OxsJSUlGQHkdmXnSkxMbPdZenq60tLSWmVPCzXjbaCA91jNLmT14U6wYA+Px+NIdryePXu2Ot6cyhxn5VrP374USWbrIDvLmZSUZHr97Nmzx/R51fe46aztDjskJibqwIED0S5Gp5KUlKS6urpoF0NS6/sRBQUFUR+SPtLKysqUnJxsuq3hdrsjlhEZ9gl2nrS6XRMSEiJ2rAQru5n7EWaZDUiSpIaGBhUUFCg/P18ul0vp6emWzoP79+8PeL6NxLDYvnVfV+z46W+/iZXfGSvlQPSZ3Rfadn71rd/MzsPMdLEWpCv9X7m57xWc3evI5XIpKyvLVCbySNRr/vbP5ubmmHn2YOexCAAAAABOsD31Qnp6ugYOHNjuQichISFmhj/pTDweT9BMMkVFRQFvHgfaHoGUlZXF5M0gAB0Lt66AM1paWjptsExdXZ2pjAje4YvtDtKVDmYxtMo3U67Z6cy2TXJzc5WamhrwAXWgAF74V11dHbE6yUwdGexYjUQdaqac1dXVGjBgQNB5VVZWKj09XampqUYGFjsEOsa8GdUyMjKUnJwcct3nb/5m1ktX4sQQ1gcOHDD235aWFtsDdUO51guljreT2TrI7HnFjJqaGlPXWlbaD76Z6jpzuyNcbrebIN0Q9O3bN9pFaKWsrEyNjY2OtCs7AyttjZaWFoJ0Y1io90Stbte8vLyQymeFmbLb3Vazel+ypqZGzc3N8ng8qqqqsvTdWBjC3Xsv1psRuKsYMGCA3/3GzO90Olt0ZxoFAs4L99grKipScnJy0HkE2+9i+brXe02UlZUV5ZLEPjuvH7369u0b9B6t0/VaZ3n2YOZ45hwAAAAAIJocueuVnp6uww47TPn5+RowYIDy8/M1fPhwgnRD4M1M1pHGxkbV1tYG/Lt3e/Tu3dvUMrvrw12gM7OjroD9olmfes+/3v8HDhxo6ftNTU2mgqj69eun8vLyUIvZofr6esvfMZsVznc6s0OwBpvO5XIpLS3N1LwQ2TrJTB0ZTCTKa7YuNxPI6VtebwYWO5g5xsKp+/zN347t1901NTUZ+4Nd56bk5OSwrvVCqePtZPaYtjvbqJn1b2Ub+Waq687XcdHO0NxZVVZWRrsI7ezYsSPaRYgaK22N7ny8O8XO4KPMzMyQ7ola3a5Wg1KtSE1NNV32WGirFRUVhVSOaJfbq6yszBgZrSvIzMwMOPy7md/Zq1cvB0r1fxjxD77CPfYaGxtVV1cXdB7B9rtYqEsD8V4Tud1u7nsF4cRoFS6XK2jnHKfrtc7y7MHM8cw5AAAAAEA0OdZN35tVC+Exe3Mm2HQul8v0xacTWbwAOMuuugL2ilZ96s1q6c+ePXtM7wdJSUkaOHCgdu/e3S6rUVxcnPLy8pSenm460NWqUPbXUI4Fs9vJzHRmshDj/0SqTrJrOU6X1+z8ze6zvvNLSkoKqUwdzTOQcOo+f/Pn3GUP73q069zUUQCGlfJEk5ky2F1Os4H2ZqSmprYKnor167i4uLh2QwbbxWrmJpfLFfVsT7EgFveZWKgbosnutkBn0/bYjMSxmpCQoNzcXKWnpys5OdnvtY9VTU1NId0TtbpdndoPvEG6ZsXCcXvgwIGYKEeovNvSe163ct3ulZWVpaqqqlbfS0hIUFpaWrvPnZSVlRU0SCrQ7/Qej04Fevke74CvQPuk2fZrU1OTcW0UaL8Ott/Fch3mW7a0tDTbR2jpSpzajsHqTafrtc707CHa6woAAAAAOtJ1xtPqoswOu2RmuoSEBFPzMjsdgNhhZ10B+0SrPg00fFd6errS0tJUWlqq4uLioPOJj49Xamqq0tLSVFNTYzwsS01NVUpKitEBxKnfGcr+GsqxkJCQoP379wf9jpnf2d3PoTk5OUpISFBjY6PpfSwS7FqO0+U1O3+z+5nv/CK5DsI5DvzNP9Sy9+7dW/v373cko01n5F2PdtVT4e5TsdAmMVMGu8tp57mk7fk+1s9BAwYMkMvlUlNTkyorK1VTU2PbvM2ey73S09OVkZGhpqYm0+esrigW95n4+PiYeMAfTI8ePdTQ0GD7fO1uC/iTlJRk6XiJJN9jMz4+XvX19Y4cnwkJCcrJyVF8fHyr65r09HTFxcWpoKAg7PlH4ntOHcN9+vSxNH0snNMTExNjohyh8t2W3ut2b/ZCs+epXr16GUGu3mPIu3+3/bxnz54qLy9XY2Oj4uPj1djYqIqKClNlzc7OltvtVmNjo+Li4ozXCQkJysrKktttbgC/tr/Tt7wHDhwwNY+OeI/xpqYmJSQktDvegbb87ZOSTJ0TvNN2tF+bnUcscuLeQkdSU1O1f//+Ttkxycn1E87+Fa7O9uwhmusKAAAAADpi6qrJ4/Fo3759TpcFfng8HjU0NHT4oCohIUHNzc1BezInJCSYehg6YMAAekUDnYyddQXsY7betVuwejwxMTGk/SU5OVmS1NLS0qpd4MTvDHV/DeVYSEtLU1FRUdB55+Xl2Xau7YoSEhKUmJgol8sV8j7mFDP7RTCRKK/Z/TchIcHy+vV4PKqvrw8rm6XdbU6z8w91+w0YMEDJycnau3ev5bJ0NfHx8ca6taOesuN4sOO4DIfZ32B3Oc1ca4V63RbL56D4+Hi1tLTI5XLJ7XYrPT3d1LnXrLy8PEvz69+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      "text/plain": [
       "<Figure size 3000x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cc.pl.draw_area(\"chr9\", 91366534, 91425373, 50000, peak_data, Brd4, \"mm10\", adata = adata_cc, font_size=2, \n",
    "                plotsize = [1,1,4], name = \"Female_Brd4\",key = \"Index\",insertionkey = \"group\", \n",
    "                name_insertion1 = 'Female Insertions', name_density1 = 'Female Insertion Density',\n",
    "                name_insertion2 = 'Total Insertions', name_density2 = 'Total Insertion Density',\n",
    "                bins = 400, figsize = (30,12), peak_line = 6, title = \"Female\")\n",
    "cc.pl.draw_area(\"chr9\", 91366534, 91425373, 50000, peak_data, Brd4, \"mm10\",  adata = adata_cc, font_size=2, \n",
    "                plotsize = [1,1,4], name = \"Male_Brd4\",key = \"Index\", insertionkey = \"group\",\n",
    "                name_insertion1 = 'Male Insertions', name_density1 = 'Male Insertion Density',\n",
    "                name_insertion2 = 'Total Insertions', name_density2 = 'Total Insertion Density',\n",
    "                bins = 400, figsize = (30,12), peak_line = 6, color = \"blue\", title = \"Male\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a8e83b77-f304-40c0-8f13-53db53b4a19e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x800 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x800 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cc.pl.draw_area(\"chr12\", 56516453, 56538107, 50000, peak_data, Brd4, \"mm10\", adata = adata_cc, font_size=2, \n",
    "                plotsize = [1,1,3], name = \"Female_Brd4\", key = \"Index\",insertionkey = \"group\", bins = 200,\n",
    "                name_insertion1 = 'Female Insertions', name_density1 = 'Female Insertion Density',\n",
    "                name_insertion2 = 'Total Insertions', name_density2 = 'Total Insertion Density',\n",
    "                figsize = (30,8), peak_line = 2, title = \"Female\")\n",
    "cc.pl.draw_area(\"chr12\", 56516453, 56538107, 50000, peak_data, Brd4, \"mm10\", adata = adata_cc, font_size=2, \n",
    "                plotsize = [1,1,3], name = \"Male_Brd4\", key = \"Index\", insertionkey = \"group\", bins = 200,\n",
    "                name_insertion1 = 'Male Insertions', name_density1 = 'Male Insertion Density',\n",
    "                name_insertion2 = 'Total Insertions', name_density2 = 'Total Insertion Density',\n",
    "                figsize = (30,8), peak_line = 2, color = \"blue\", title = \"Male\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7214ae46-b6df-40ae-9cb4-c04a17f78fed",
   "metadata": {},
   "source": [
    "We can now plot a volcano plot to visualize the distribution of differentially bound peaks. labelright and labellest are the location points of the labels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ec518973-adc1-4f00-8e51-c4399a83ae04",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/juanru/Desktop/pycallingcards/pycallingcards/pycallingcards/plotting/_volcano.py:70: RuntimeWarning: divide by zero encountered in log10\n",
      "  pva = -np.log10(np.array(adata_cc.uns[name][pvalue_name].tolist())[:, 1])\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cc.pl.volcano_plot(adata_cc, pvalue_name = 'pvalues_adj', pvalue_cutoff = 0.01, lfc_cutoff = 4,\n",
    "                   figsize = (5,4), labelright = (3,250), labelleft = (-9,250))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de407982-cd06-40f9-9313-ec24e4ffeeaf",
   "metadata": {},
   "source": [
    "We can now use [HOMER](http://homer.ucsd.edu/homer/motif/) to call motifs for both female and male bound peaks separately to find out potential motif binding difference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "f8bb9bb5-50ea-4659-88e4-d716a7624804",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There is no save_name, it will save to temp_Homer_trial.bed and then delete.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "\tPosition file = temp_Homer_trial.bed\n",
      "\tGenome = mm10\n",
      "\tOutput Directory = Homer/GBM_female\n",
      "\tFragment size set to 1000\n",
      "\tUsing 12 CPUs\n",
      "\tWill not run homer for de novo motifs\n",
      "\tFound mset for \"mouse\", will check against vertebrates motifs\n",
      "\tPeak/BED file conversion summary:\n",
      "\t\tBED/Header formatted lines: 1009\n",
      "\t\tpeakfile formatted lines: 0\n",
      "\n",
      "\tPeak File Statistics:\n",
      "\t\tTotal Peaks: 1009\n",
      "\t\tRedundant Peak IDs: 0\n",
      "\t\tPeaks lacking information: 0 (need at least 5 columns per peak)\n",
      "\t\tPeaks with misformatted coordinates: 0 (should be integer)\n",
      "\t\tPeaks with misformatted strand: 0 (should be either +/- or 0/1)\n",
      "\n",
      "\tPeak file looks good!\n",
      "\n",
      "\tBackground files for 1000 bp fragments found.\n",
      "\tCustom genome sequence directory: /home/juanru/miniconda3/share/homer/.//data/genomes/mm10//\n",
      "\n",
      "\tExtracting sequences from directory: /home/juanru/miniconda3/share/homer/.//data/genomes/mm10//\n",
      "\tExtracting 96 sequences from chr1\n",
      "\tExtracting 93 sequences from chr2\n",
      "\tExtracting 62 sequences from chr3\n",
      "\tExtracting 39 sequences from chr4\n",
      "\tExtracting 67 sequences from chr5\n",
      "\tExtracting 66 sequences from chr6\n",
      "\tExtracting 62 sequences from chr7\n",
      "\tExtracting 45 sequences from chr8\n",
      "\tExtracting 59 sequences from chr9\n",
      "\tExtracting 50 sequences from chr10\n",
      "\tExtracting 41 sequences from chr11\n",
      "\tExtracting 41 sequences from chr12\n",
      "\tExtracting 46 sequences from chr13\n",
      "\tExtracting 25 sequences from chr14\n",
      "\tExtracting 26 sequences from chr15\n",
      "\tExtracting 40 sequences from chr16\n",
      "\tExtracting 40 sequences from chr17\n",
      "\tExtracting 32 sequences from chr18\n",
      "\tExtracting 32 sequences from chr19\n",
      "\tExtracting 47 sequences from chrX\n",
      "\n",
      "\tNot removing redundant sequences\n",
      "\n",
      "\n",
      "\tSequences processed:\n",
      "\t\tAuto detected maximum sequence length of 1001 bp\n",
      "\t\t1009 total\n",
      "\n",
      "\tFrequency Bins: 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.6 0.7 0.8\n",
      "\tFreq\tBin\tCount\n",
      "\t0.3\t2\t14\n",
      "\t0.35\t3\t101\n",
      "\t0.4\t4\t317\n",
      "\t0.45\t5\t309\n",
      "\t0.5\t6\t201\n",
      "\t0.6\t7\t66\n",
      "\t0.7\t8\t1\n",
      "\n",
      "\tTotal sequences set to 50000\n",
      "\n",
      "\tChoosing background that matches in CpG/GC content...\n",
      "\tBin\t# Targets\t# Background\tBackground Weight\n",
      "\t2\t14\t680\t1.000\n",
      "\t3\t101\t4904\t1.000\n",
      "\t4\t317\t15392\t1.000\n",
      "\t5\t309\t15003\t1.000\n",
      "\t6\t201\t9759\t1.000\n",
      "\t7\t66\t3205\t1.000\n",
      "\t8\t1\t49\t0.991\n",
      "\tAssembling sequence file...\n",
      "\tNormalizing lower order oligos using homer2\n",
      "\n",
      "\tReading input files...\n",
      "\t50001 total sequences read\n",
      "\tAutonormalization: 1-mers (4 total)\n",
      "\t\tA\t29.26%\t29.21%\t1.001\n",
      "\t\tC\t20.74%\t20.79%\t0.998\n",
      "\t\tG\t20.74%\t20.79%\t0.998\n",
      "\t\tT\t29.26%\t29.21%\t1.001\n",
      "\tAutonormalization: 2-mers (16 total)\n",
      "\t\tAA\t9.53%\t9.22%\t1.034\n",
      "\t\tCA\t7.34%\t7.44%\t0.987\n",
      "\t\tGA\t6.15%\t6.15%\t1.001\n",
      "\t\tTA\t6.23%\t6.41%\t0.972\n",
      "\t\tAC\t5.27%\t5.38%\t0.980\n",
      "\t\tCC\t5.08%\t5.17%\t0.983\n",
      "\t\tGC\t4.24%\t4.08%\t1.037\n",
      "\t\tTC\t6.15%\t6.15%\t1.001\n",
      "\t\tAG\t7.36%\t7.34%\t1.003\n",
      "\t\tCG\t0.96%\t0.84%\t1.148\n",
      "\t\tGG\t5.08%\t5.17%\t0.983\n",
      "\t\tTG\t7.34%\t7.44%\t0.987\n",
      "\t\tAT\t7.09%\t7.28%\t0.974\n",
      "\t\tCT\t7.36%\t7.34%\t1.003\n",
      "\t\tGT\t5.27%\t5.38%\t0.980\n",
      "\t\tTT\t9.53%\t9.22%\t1.034\n",
      "\tAutonormalization: 3-mers (64 total)\n",
      "\tNormalization weights can be found in file: Homer/GBM_female/seq.autonorm.tsv\n",
      "\tConverging on autonormalization solution:\n",
      "\t...............................................................................\n",
      "\tFinal normalization:\tAutonormalization: 1-mers (4 total)\n",
      "\t\tA\t29.26%\t29.24%\t1.001\n",
      "\t\tC\t20.74%\t20.76%\t0.999\n",
      "\t\tG\t20.74%\t20.76%\t0.999\n",
      "\t\tT\t29.26%\t29.24%\t1.001\n",
      "\tAutonormalization: 2-mers (16 total)\n",
      "\t\tAA\t9.53%\t9.41%\t1.013\n",
      "\t\tCA\t7.34%\t7.35%\t0.998\n",
      "\t\tGA\t6.15%\t6.14%\t1.001\n",
      "\t\tTA\t6.23%\t6.33%\t0.985\n",
      "\t\tAC\t5.27%\t5.32%\t0.991\n",
      "\t\tCC\t5.08%\t5.14%\t0.989\n",
      "\t\tGC\t4.24%\t4.16%\t1.018\n",
      "\t\tTC\t6.15%\t6.14%\t1.001\n",
      "\t\tAG\t7.36%\t7.34%\t1.002\n",
      "\t\tCG\t0.96%\t0.93%\t1.033\n",
      "\t\tGG\t5.08%\t5.14%\t0.989\n",
      "\t\tTG\t7.34%\t7.35%\t0.998\n",
      "\t\tAT\t7.09%\t7.16%\t0.990\n",
      "\t\tCT\t7.36%\t7.34%\t1.002\n",
      "\t\tGT\t5.27%\t5.32%\t0.991\n",
      "\t\tTT\t9.53%\t9.41%\t1.013\n",
      "\tAutonormalization: 3-mers (64 total)\n",
      "\tFinished preparing sequence/group files\n",
      "\n",
      "\t----------------------------------------------------------\n",
      "\tKnown motif enrichment\n",
      "\n",
      "\tReading input files...\n",
      "\t50001 total sequences read\n",
      "\t440 motifs loaded\n",
      "\tCache length = 11180\n",
      "\tUsing binomial scoring\n",
      "\tChecking enrichment of 440 motif(s)\n",
      "\t|0%                                    50%                                  100%|\n",
      "\t=================================================================================\n",
      "\tPreparing HTML output with sequence logos...\n",
      "\t\t1 of 440 (1e-18) Chop(bZIP)/MEF-Chop-ChIP-Seq(GSE35681)/Homer\n",
      "\t\t2 of 440 (1e-17) Atf4(bZIP)/MEF-Atf4-ChIP-Seq(GSE35681)/Homer\n",
      "\t\t3 of 440 (1e-17) ISRE(IRF)/ThioMac-LPS-Expression(GSE23622)/Homer\n",
      "\t\t4 of 440 (1e-15) Atf3(bZIP)/GBM-ATF3-ChIP-Seq(GSE33912)/Homer\n",
      "\t\t5 of 440 (1e-15) Fos(bZIP)/TSC-Fos-ChIP-Seq(GSE110950)/Homer\n",
      "\t\t6 of 440 (1e-15) AP-1(bZIP)/ThioMac-PU.1-ChIP-Seq(GSE21512)/Homer\n",
      "\t\t7 of 440 (1e-15) JunB(bZIP)/DendriticCells-Junb-ChIP-Seq(GSE36099)/Homer\n",
      "\t\t8 of 440 (1e-14) Fra1(bZIP)/BT549-Fra1-ChIP-Seq(GSE46166)/Homer\n",
      "\t\t9 of 440 (1e-13) BATF(bZIP)/Th17-BATF-ChIP-Seq(GSE39756)/Homer\n",
      "\t\t10 of 440 (1e-13) IRF2(IRF)/Erythroblas-IRF2-ChIP-Seq(GSE36985)/Homer\n",
      "\t\t11 of 440 (1e-12) IRF3(IRF)/BMDM-Irf3-ChIP-Seq(GSE67343)/Homer\n",
      "\t\t12 of 440 (1e-12) IRF8(IRF)/BMDM-IRF8-ChIP-Seq(GSE77884)/Homer\n",
      "\t\t13 of 440 (1e-11) Fra2(bZIP)/Striatum-Fra2-ChIP-Seq(GSE43429)/Homer\n",
      "\t\t14 of 440 (1e-11) Fosl2(bZIP)/3T3L1-Fosl2-ChIP-Seq(GSE56872)/Homer\n",
      "\t\t15 of 440 (1e-10) Jun-AP1(bZIP)/K562-cJun-ChIP-Seq(GSE31477)/Homer\n",
      "\t\t16 of 440 (1e-9) IRF1(IRF)/PBMC-IRF1-ChIP-Seq(GSE43036)/Homer\n",
      "\t\t17 of 440 (1e-7) CEBP:AP1(bZIP)/ThioMac-CEBPb-ChIP-Seq(GSE21512)/Homer\n",
      "\t\t18 of 440 (1e-7) Rbpj1(?)/Panc1-Rbpj1-ChIP-Seq(GSE47459)/Homer\n",
      "\t\t19 of 440 (1e-7) TEAD1(TEAD)/HepG2-TEAD1-ChIP-Seq(Encode)/Homer\n",
      "\t\t20 of 440 (1e-6) PU.1:IRF8(ETS:IRF)/pDC-Irf8-ChIP-Seq(GSE66899)/Homer\n",
      "\t\t21 of 440 (1e-6) GABPA(ETS)/Jurkat-GABPa-ChIP-Seq(GSE17954)/Homer\n",
      "\t\t22 of 440 (1e-6) Zic3(Zf)/mES-Zic3-ChIP-Seq(GSE37889)/Homer\n",
      "\t\t23 of 440 (1e-5) Unknown-ESC-element(?)/mES-Nanog-ChIP-Seq(GSE11724)/Homer\n",
      "\t\t24 of 440 (1e-4) ETS1(ETS)/Jurkat-ETS1-ChIP-Seq(GSE17954)/Homer\n",
      "\t\t25 of 440 (1e-4) NF1-halfsite(CTF)/LNCaP-NF1-ChIP-Seq(Unpublished)/Homer\n",
      "\t\t26 of 440 (1e-4) Mef2c(MADS)/GM12878-Mef2c-ChIP-Seq(GSE32465)/Homer\n",
      "\t\t27 of 440 (1e-4) TEAD(TEA)/Fibroblast-PU.1-ChIP-Seq(Unpublished)/Homer\n",
      "\t\t28 of 440 (1e-4) Isl1(Homeobox)/Neuron-Isl1-ChIP-Seq(GSE31456)/Homer\n",
      "\t\t29 of 440 (1e-4) STAT5(Stat)/mCD4+-Stat5-ChIP-Seq(GSE12346)/Homer\n",
      "\t\t30 of 440 (1e-4) TEAD3(TEA)/HepG2-TEAD3-ChIP-Seq(Encode)/Homer\n",
      "\t\t31 of 440 (1e-4) CEBP:CEBP(bZIP)/MEF-Chop-ChIP-Seq(GSE35681)/Homer\n",
      "\t\t32 of 440 (1e-4) TEAD4(TEA)/Tropoblast-Tead4-ChIP-Seq(GSE37350)/Homer\n",
      "\t\t33 of 440 (1e-4) Pitx1:Ebox(Homeobox,bHLH)/Hindlimb-Pitx1-ChIP-Seq(GSE41591)/Homer\n",
      "\t\t34 of 440 (1e-4) PAX6(Paired,Homeobox)/Forebrain-Pax6-ChIP-Seq(GSE66961)/Homer\n",
      "\t\t35 of 440 (1e-4) Smad4(MAD)/ESC-SMAD4-ChIP-Seq(GSE29422)/Homer\n",
      "\t\t36 of 440 (1e-4) Dlx3(Homeobox)/Kerainocytes-Dlx3-ChIP-Seq(GSE89884)/Homer\n",
      "\t\t37 of 440 (1e-4) Fli1(ETS)/CD8-FLI-ChIP-Seq(GSE20898)/Homer\n",
      "\t\t38 of 440 (1e-4) CREB5(bZIP)/LNCaP-CREB5.V5-ChIP-Seq(GSE137775)/Homer\n",
      "\t\t39 of 440 (1e-3) EWS:FLI1-fusion(ETS)/SK_N_MC-EWS:FLI1-ChIP-Seq(SRA014231)/Homer\n",
      "\t\t40 of 440 (1e-3) Bach2(bZIP)/OCILy7-Bach2-ChIP-Seq(GSE44420)/Homer\n",
      "\t\t41 of 440 (1e-3) STAT4(Stat)/CD4-Stat4-ChIP-Seq(GSE22104)/Homer\n",
      "\t\t42 of 440 (1e-3) IRF4(IRF)/GM12878-IRF4-ChIP-Seq(GSE32465)/Homer\n",
      "\t\t43 of 440 (1e-3) Etv2(ETS)/ES-ER71-ChIP-Seq(GSE59402)/Homer\n",
      "\t\t44 of 440 (1e-3) HLF(bZIP)/HSC-HLF.Flag-ChIP-Seq(GSE69817)/Homer\n",
      "\t\t45 of 440 (1e-3) c-Jun-CRE(bZIP)/K562-cJun-ChIP-Seq(GSE31477)/Homer\n",
      "\t\t46 of 440 (1e-3) AMYB(HTH)/Testes-AMYB-ChIP-Seq(GSE44588)/Homer\n",
      "\t\t47 of 440 (1e-3) EWS:ERG-fusion(ETS)/CADO_ES1-EWS:ERG-ChIP-Seq(SRA014231)/Homer\n",
      "\t\t48 of 440 (1e-3) TEAD2(TEA)/Py2T-Tead2-ChIP-Seq(GSE55709)/Homer\n",
      "\t\t49 of 440 (1e-3) NFIL3(bZIP)/HepG2-NFIL3-ChIP-Seq(Encode)/Homer\n",
      "\t\t50 of 440 (1e-3) ETV1(ETS)/GIST48-ETV1-ChIP-Seq(GSE22441)/Homer\n",
      "\t\t51 of 440 (1e-3) Zic(Zf)/Cerebellum-ZIC1.2-ChIP-Seq(GSE60731)/Homer\n",
      "\t\t52 of 440 (1e-3) Mef2a(MADS)/HL1-Mef2a.biotin-ChIP-Seq(GSE21529)/Homer\n",
      "\t\t53 of 440 (1e-3) Elf4(ETS)/BMDM-Elf4-ChIP-Seq(GSE88699)/Homer\n",
      "\t\t54 of 440 (1e-3) CArG(MADS)/PUER-Srf-ChIP-Seq(Sullivan_et_al.)/Homer\n",
      "\t\t55 of 440 (1e-3) Elk1(ETS)/Hela-Elk1-ChIP-Seq(GSE31477)/Homer\n",
      "\t\t56 of 440 (1e-2) MafA(bZIP)/Islet-MafA-ChIP-Seq(GSE30298)/Homer\n",
      "\t\t57 of 440 (1e-2) MYB(HTH)/ERMYB-Myb-ChIPSeq(GSE22095)/Homer\n",
      "\t\t58 of 440 (1e-2) PU.1-IRF(ETS:IRF)/Bcell-PU.1-ChIP-Seq(GSE21512)/Homer\n",
      "\t\t59 of 440 (1e-2) EBF1(EBF)/Near-E2A-ChIP-Seq(GSE21512)/Homer\n",
      "\t\t60 of 440 (1e-2) DLX5(Homeobox)/BasalGanglia-Dlx5-ChIP-seq(GSE124936)/Homer\n",
      "\t\t61 of 440 (1e-2) Zic2(Zf)/ESC-Zic2-ChIP-Seq(SRP197560)/Homer\n",
      "\t\t62 of 440 (1e-2) DLX1(Homeobox)/BasalGanglia-Dlx1-ChIP-seq(GSE124936)/Homer\n",
      "\t\t63 of 440 (1e-2) Six2(Homeobox)/NephronProgenitor-Six2-ChIP-Seq(GSE39837)/Homer\n",
      "\t\t64 of 440 (1e-2) STAT6(Stat)/Macrophage-Stat6-ChIP-Seq(GSE38377)/Homer\n",
      "\t\t65 of 440 (1e-2) NFAT:AP1(RHD,bZIP)/Jurkat-NFATC1-ChIP-Seq(Jolma_et_al.)/Homer\n",
      "\t\t66 of 440 (1e-2) Fox:Ebox(Forkhead,bHLH)/Panc1-Foxa2-ChIP-Seq(GSE47459)/Homer\n",
      "\t\t67 of 440 (1e-2) Stat3(Stat)/mES-Stat3-ChIP-Seq(GSE11431)/Homer\n",
      "\t\t68 of 440 (1e-2) NFkB-p65-Rel(RHD)/ThioMac-LPS-Expression(GSE23622)/Homer\n",
      "\t\t69 of 440 (1e-2) EHF(ETS)/LoVo-EHF-ChIP-Seq(GSE49402)/Homer\n",
      "\t\t70 of 440 (1e-2) Hoxd11(Homeobox)/ChickenMSG-Hoxd11.Flag-ChIP-Seq(GSE86088)/Homer\n",
      "\t\t71 of 440 (1e-2) IRF:BATF(IRF:bZIP)/pDC-Irf8-ChIP-Seq(GSE66899)/Homer\n",
      "\t\t72 of 440 (1e-2) ETV4(ETS)/HepG2-ETV4-ChIP-Seq(ENCODE)/Homer\n",
      "\t\t73 of 440 (1e-2) Smad2(MAD)/ES-SMAD2-ChIP-Seq(GSE29422)/Homer\n",
      "\t\t74 of 440 (1e-2) STAT6(Stat)/CD4-Stat6-ChIP-Seq(GSE22104)/Homer\n",
      "\t\t75 of 440 (1e-2) Prop1(Homeobox)/GHFT1-PROP1.biotin-ChIP-Seq(GSE77302)/Homer\n",
      "\t\t76 of 440 (1e-2) Brn2(POU,Homeobox)/NPC-Brn2-ChIP-Seq(GSE35496)/Homer\n",
      "\t\t77 of 440 (1e-2) NFkB-p65(RHD)/GM12787-p65-ChIP-Seq(GSE19485)/Homer\n",
      "\t\t78 of 440 (1e-2) ETS:E-box(ETS,bHLH)/HPC7-Scl-ChIP-Seq(GSE22178)/Homer\n",
      "\t\t79 of 440 (1e-2) PU.1(ETS)/ThioMac-PU.1-ChIP-Seq(GSE21512)/Homer\n",
      "\t\t80 of 440 (1e-2) Nkx6.1(Homeobox)/Islet-Nkx6.1-ChIP-Seq(GSE40975)/Homer\n",
      "\t\t81 of 440 (1e-2) Mef2d(MADS)/Retina-Mef2d-ChIP-Seq(GSE61391)/Homer\n",
      "\tSkipping...\n",
      "\tJob finished - if results look good, please send beer to ..\n",
      "\n",
      "\tCleaning up tmp files...\n",
      "\n",
      "\n",
      "\tPosition file = temp_Homer_trial.bed\n",
      "\tGenome = mm10\n",
      "\tOutput Directory = Homer/GBM_male\n",
      "\tFragment size set to 1000\n",
      "\tUsing 12 CPUs\n",
      "\tWill not run homer for de novo motifs\n",
      "\tFound mset for \"mouse\", will check against vertebrates motifs\n",
      "\tPeak/BED file conversion summary:\n",
      "\t\tBED/Header formatted lines: 585\n",
      "\t\tpeakfile formatted lines: 0\n",
      "\n",
      "\tPeak File Statistics:\n",
      "\t\tTotal Peaks: 585\n",
      "\t\tRedundant Peak IDs: 0\n",
      "\t\tPeaks lacking information: 0 (need at least 5 columns per peak)\n",
      "\t\tPeaks with misformatted coordinates: 0 (should be integer)\n",
      "\t\tPeaks with misformatted strand: 0 (should be either +/- or 0/1)\n",
      "\n",
      "\tPeak file looks good!\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Finished!\n",
      "There is no save_name, it will save to temp_Homer_trial.bed and then delete.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\tBackground files for 1000 bp fragments found.\n",
      "\tCustom genome sequence directory: /home/juanru/miniconda3/share/homer/.//data/genomes/mm10//\n",
      "\n",
      "\tExtracting sequences from directory: /home/juanru/miniconda3/share/homer/.//data/genomes/mm10//\n",
      "\tExtracting 36 sequences from chr1\n",
      "\tExtracting 40 sequences from chr2\n",
      "\tExtracting 33 sequences from chr3\n",
      "\tExtracting 20 sequences from chr4\n",
      "\tExtracting 28 sequences from chr5\n",
      "\tExtracting 35 sequences from chr6\n",
      "\tExtracting 18 sequences from chr7\n",
      "\tExtracting 25 sequences from chr8\n",
      "\tExtracting 21 sequences from chr9\n",
      "\tExtracting 52 sequences from chr10\n",
      "\tExtracting 39 sequences from chr11\n",
      "\tExtracting 26 sequences from chr12\n",
      "\tExtracting 23 sequences from chr13\n",
      "\tExtracting 36 sequences from chr14\n",
      "\tExtracting 43 sequences from chr15\n",
      "\tExtracting 18 sequences from chr16\n",
      "\tExtracting 17 sequences from chr17\n",
      "\tExtracting 28 sequences from chr18\n",
      "\tExtracting 22 sequences from chr19\n",
      "\tExtracting 21 sequences from chrX\n",
      "\tExtracting 4 sequences from chrY\n",
      "\n",
      "\tNot removing redundant sequences\n",
      "\n",
      "\n",
      "\tSequences processed:\n",
      "\t\tAuto detected maximum sequence length of 1001 bp\n",
      "\t\t585 total\n",
      "\n",
      "\tFrequency Bins: 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.6 0.7 0.8\n",
      "\tFreq\tBin\tCount\n",
      "\t0.3\t2\t2\n",
      "\t0.35\t3\t41\n",
      "\t0.4\t4\t134\n",
      "\t0.45\t5\t215\n",
      "\t0.5\t6\t133\n",
      "\t0.6\t7\t56\n",
      "\t0.7\t8\t4\n",
      "\n",
      "\tTotal sequences set to 50000\n",
      "\n",
      "\tChoosing background that matches in CpG/GC content...\n",
      "\tBin\t# Targets\t# Background\tBackground Weight\n",
      "\t2\t2\t169\t1.000\n",
      "\t3\t41\t3463\t1.000\n",
      "\t4\t134\t11319\t1.000\n",
      "\t5\t215\t18161\t1.000\n",
      "\t6\t133\t11235\t1.000\n",
      "\t7\t56\t4730\t1.000\n",
      "\t8\t4\t338\t1.000\n",
      "\tAssembling sequence file...\n",
      "\tNormalizing lower order oligos using homer2\n",
      "\n",
      "\tReading input files...\n",
      "\t50000 total sequences read\n",
      "\tAutonormalization: 1-mers (4 total)\n",
      "\t\tA\t28.57%\t28.51%\t1.002\n",
      "\t\tC\t21.43%\t21.49%\t0.997\n",
      "\t\tG\t21.43%\t21.49%\t0.997\n",
      "\t\tT\t28.57%\t28.51%\t1.002\n",
      "\tAutonormalization: 2-mers (16 total)\n",
      "\t\tAA\t9.11%\t8.75%\t1.041\n",
      "\t\tCA\t7.48%\t7.54%\t0.993\n",
      "\t\tGA\t6.12%\t6.21%\t0.985\n",
      "\t\tTA\t5.87%\t6.02%\t0.974\n",
      "\t\tAC\t5.39%\t5.41%\t0.995\n",
      "\t\tCC\t5.41%\t5.51%\t0.982\n",
      "\t\tGC\t4.51%\t4.35%\t1.035\n",
      "\t\tTC\t6.12%\t6.21%\t0.985\n",
      "\t\tAG\t7.40%\t7.49%\t0.988\n",
      "\t\tCG\t1.13%\t0.95%\t1.196\n",
      "\t\tGG\t5.41%\t5.51%\t0.982\n",
      "\t\tTG\t7.48%\t7.54%\t0.993\n",
      "\t\tAT\t6.67%\t6.86%\t0.973\n",
      "\t\tCT\t7.40%\t7.49%\t0.988\n",
      "\t\tGT\t5.39%\t5.41%\t0.995\n",
      "\t\tTT\t9.11%\t8.75%\t1.041\n",
      "\tAutonormalization: 3-mers (64 total)\n",
      "\tNormalization weights can be found in file: Homer/GBM_male/seq.autonorm.tsv\n",
      "\tConverging on autonormalization solution:\n",
      "\t...............................................................................\n",
      "\tFinal normalization:\tAutonormalization: 1-mers (4 total)\n",
      "\t\tA\t28.57%\t28.55%\t1.001\n",
      "\t\tC\t21.43%\t21.45%\t0.999\n",
      "\t\tG\t21.43%\t21.45%\t0.999\n",
      "\t\tT\t28.57%\t28.55%\t1.001\n",
      "\tAutonormalization: 2-mers (16 total)\n",
      "\t\tAA\t9.11%\t8.97%\t1.016\n",
      "\t\tCA\t7.48%\t7.47%\t1.001\n",
      "\t\tGA\t6.12%\t6.15%\t0.995\n",
      "\t\tTA\t5.87%\t5.97%\t0.983\n",
      "\t\tAC\t5.39%\t5.40%\t0.998\n",
      "\t\tCC\t5.41%\t5.46%\t0.992\n",
      "\t\tGC\t4.51%\t4.44%\t1.014\n",
      "\t\tTC\t6.12%\t6.15%\t0.995\n",
      "\t\tAG\t7.40%\t7.42%\t0.997\n",
      "\t\tCG\t1.13%\t1.10%\t1.033\n",
      "\t\tGG\t5.41%\t5.46%\t0.992\n",
      "\t\tTG\t7.48%\t7.47%\t1.001\n",
      "\t\tAT\t6.67%\t6.77%\t0.986\n",
      "\t\tCT\t7.40%\t7.42%\t0.997\n",
      "\t\tGT\t5.39%\t5.40%\t0.998\n",
      "\t\tTT\t9.11%\t8.97%\t1.016\n",
      "\tAutonormalization: 3-mers (64 total)\n",
      "\tFinished preparing sequence/group files\n",
      "\n",
      "\t----------------------------------------------------------\n",
      "\tKnown motif enrichment\n",
      "\n",
      "\tReading input files...\n",
      "\t50000 total sequences read\n",
      "\t440 motifs loaded\n",
      "\tCache length = 11180\n",
      "\tUsing binomial scoring\n",
      "\tChecking enrichment of 440 motif(s)\n",
      "\t|0%                                    50%                                  100%|\n",
      "\t================================================================================="
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Finished!\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "\tPreparing HTML output with sequence logos...\n",
      "\t\t1 of 440 (1e-42) Fosl2(bZIP)/3T3L1-Fosl2-ChIP-Seq(GSE56872)/Homer\n",
      "\t\t2 of 440 (1e-41) Jun-AP1(bZIP)/K562-cJun-ChIP-Seq(GSE31477)/Homer\n",
      "\t\t3 of 440 (1e-39) Fos(bZIP)/TSC-Fos-ChIP-Seq(GSE110950)/Homer\n",
      "\t\t4 of 440 (1e-38) JunB(bZIP)/DendriticCells-Junb-ChIP-Seq(GSE36099)/Homer\n",
      "\t\t5 of 440 (1e-37) Fra1(bZIP)/BT549-Fra1-ChIP-Seq(GSE46166)/Homer\n",
      "\t\t6 of 440 (1e-35) Fra2(bZIP)/Striatum-Fra2-ChIP-Seq(GSE43429)/Homer\n",
      "\t\t7 of 440 (1e-35) BATF(bZIP)/Th17-BATF-ChIP-Seq(GSE39756)/Homer\n",
      "\t\t8 of 440 (1e-34) Atf3(bZIP)/GBM-ATF3-ChIP-Seq(GSE33912)/Homer\n",
      "\t\t9 of 440 (1e-34) AP-1(bZIP)/ThioMac-PU.1-ChIP-Seq(GSE21512)/Homer\n",
      "\t\t10 of 440 (1e-22) Bach2(bZIP)/OCILy7-Bach2-ChIP-Seq(GSE44420)/Homer\n",
      "\t\t11 of 440 (1e-10) Nrf2(bZIP)/Lymphoblast-Nrf2-ChIP-Seq(GSE37589)/Homer\n",
      "\t\t12 of 440 (1e-9) NF-E2(bZIP)/K562-NFE2-ChIP-Seq(GSE31477)/Homer\n",
      "\t\t13 of 440 (1e-7) Bach1(bZIP)/K562-Bach1-ChIP-Seq(GSE31477)/Homer\n",
      "\t\t14 of 440 (1e-7) NFE2L2(bZIP)/HepG2-NFE2L2-ChIP-Seq(Encode)/Homer\n",
      "\t\t15 of 440 (1e-6) MafK(bZIP)/C2C12-MafK-ChIP-Seq(GSE36030)/Homer\n",
      "\t\t16 of 440 (1e-5) Ets1-distal(ETS)/CD4+-PolII-ChIP-Seq(Barski_et_al.)/Homer\n",
      "\t\t17 of 440 (1e-4) Isl1(Homeobox)/Neuron-Isl1-ChIP-Seq(GSE31456)/Homer\n",
      "\t\t18 of 440 (1e-4) Sox3(HMG)/NPC-Sox3-ChIP-Seq(GSE33059)/Homer\n",
      "\t\t19 of 440 (1e-3) Bapx1(Homeobox)/VertebralCol-Bapx1-ChIP-Seq(GSE36672)/Homer\n",
      "\t\t20 of 440 (1e-3) Fli1(ETS)/CD8-FLI-ChIP-Seq(GSE20898)/Homer\n",
      "\t\t21 of 440 (1e-3) MafA(bZIP)/Islet-MafA-ChIP-Seq(GSE30298)/Homer\n",
      "\t\t22 of 440 (1e-3) Fox:Ebox(Forkhead,bHLH)/Panc1-Foxa2-ChIP-Seq(GSE47459)/Homer\n",
      "\t\t23 of 440 (1e-3) Nkx2.2(Homeobox)/NPC-Nkx2.2-ChIP-Seq(GSE61673)/Homer\n",
      "\t\t24 of 440 (1e-3) Sox10(HMG)/SciaticNerve-Sox3-ChIP-Seq(GSE35132)/Homer\n",
      "\t\t25 of 440 (1e-3) LHX9(Homeobox)/Hct116-LHX9.V5-ChIP-Seq(GSE116822)/Homer\n",
      "\t\t26 of 440 (1e-3) TATA-Box(TBP)/Promoter/Homer\n",
      "\t\t27 of 440 (1e-3) KLF14(Zf)/HEK293-KLF14.GFP-ChIP-Seq(GSE58341)/Homer\n",
      "\t\t28 of 440 (1e-2) ZNF669(Zf)/HEK293-ZNF669.GFP-ChIP-Seq(GSE58341)/Homer\n",
      "\t\t29 of 440 (1e-2) Lhx2(Homeobox)/HFSC-Lhx2-ChIP-Seq(GSE48068)/Homer\n",
      "\t\t30 of 440 (1e-2) Sox4(HMG)/proB-Sox4-ChIP-Seq(GSE50066)/Homer\n",
      "\t\t31 of 440 (1e-2) DLX5(Homeobox)/BasalGanglia-Dlx5-ChIP-seq(GSE124936)/Homer\n",
      "\t\t32 of 440 (1e-2) RUNX-AML(Runt)/CD4+-PolII-ChIP-Seq(Barski_et_al.)/Homer\n",
      "\t\t33 of 440 (1e-2) Sp5(Zf)/mES-Sp5.Flag-ChIP-Seq(GSE72989)/Homer\n",
      "\t\t34 of 440 (1e-2) EWS:ERG-fusion(ETS)/CADO_ES1-EWS:ERG-ChIP-Seq(SRA014231)/Homer\n",
      "\t\t35 of 440 (1e-2) RUNX1(Runt)/Jurkat-RUNX1-ChIP-Seq(GSE29180)/Homer\n",
      "\t\t36 of 440 (1e-2) Etv2(ETS)/ES-ER71-ChIP-Seq(GSE59402)/Homer\n",
      "\t\t37 of 440 (1e-2) ETV4(ETS)/HepG2-ETV4-ChIP-Seq(ENCODE)/Homer\n",
      "\t\t38 of 440 (1e-2) Sox2(HMG)/mES-Sox2-ChIP-Seq(GSE11431)/Homer\n",
      "\t\t39 of 440 (1e-2) ETS1(ETS)/Jurkat-ETS1-ChIP-Seq(GSE17954)/Homer\n",
      "\t\t40 of 440 (1e-2) Brn1(POU,Homeobox)/NPC-Brn1-ChIP-Seq(GSE35496)/Homer\n",
      "\t\t41 of 440 (1e-2) CHR(?)/Hela-CellCycle-Expression/Homer\n",
      "\t\t42 of 440 (1e-2) Dlx3(Homeobox)/Kerainocytes-Dlx3-ChIP-Seq(GSE89884)/Homer\n",
      "\t\t43 of 440 (1e-2) EWS:FLI1-fusion(ETS)/SK_N_MC-EWS:FLI1-ChIP-Seq(SRA014231)/Homer\n",
      "\t\t44 of 440 (1e-2) KLF3(Zf)/MEF-Klf3-ChIP-Seq(GSE44748)/Homer\n",
      "\t\t45 of 440 (1e-2) STAT5(Stat)/mCD4+-Stat5-ChIP-Seq(GSE12346)/Homer\n",
      "\t\t46 of 440 (1e-2) Elk4(ETS)/Hela-Elk4-ChIP-Seq(GSE31477)/Homer\n",
      "\t\t47 of 440 (1e-2) Tbx20(T-box)/Heart-Tbx20-ChIP-Seq(GSE29636)/Homer\n",
      "\t\t48 of 440 (1e-2) Rfx6(HTH)/Min6b1-Rfx6.HA-ChIP-Seq(GSE62844)/Homer\n",
      "\t\t49 of 440 (1e-2) ETS:RUNX(ETS,Runt)/Jurkat-RUNX1-ChIP-Seq(GSE17954)/Homer\n",
      "\t\t50 of 440 (1e-2) AMYB(HTH)/Testes-AMYB-ChIP-Seq(GSE44588)/Homer\n",
      "\t\t51 of 440 (1e-2) Lhx1(Homeobox)/EmbryoCarcinoma-Lhx1-ChIP-Seq(GSE70957)/Homer\n",
      "\t\t52 of 440 (1e-2) Lhx3(Homeobox)/Neuron-Lhx3-ChIP-Seq(GSE31456)/Homer\n",
      "\t\t53 of 440 (1e-2) DLX2(Homeobox)/BasalGanglia-Dlx2-ChIP-seq(GSE124936)/Homer\n",
      "\t\t54 of 440 (1e-2) Nkx6.1(Homeobox)/Islet-Nkx6.1-ChIP-Seq(GSE40975)/Homer\n",
      "\t\t55 of 440 (1e-2) OCT4-SOX2-TCF-NANOG(POU,Homeobox,HMG)/mES-Oct4-ChIP-Seq(GSE11431)/Homer\n",
      "\t\t56 of 440 (1e-2) Sox7(HMG)/ESC-Sox7-ChIP-Seq(GSE133899)/Homer\n",
      "\t\t57 of 440 (1e-2) Sox6(HMG)/Myotubes-Sox6-ChIP-Seq(GSE32627)/Homer\n",
      "\t\t58 of 440 (1e-2) DLX1(Homeobox)/BasalGanglia-Dlx1-ChIP-seq(GSE124936)/Homer\n",
      "\t\t59 of 440 (1e-2) AP-2alpha(AP2)/Hela-AP2alpha-ChIP-Seq(GSE31477)/Homer\n",
      "\t\t60 of 440 (1e-2) GABPA(ETS)/Jurkat-GABPa-ChIP-Seq(GSE17954)/Homer\n",
      "\t\t61 of 440 (1e-2) Maz(Zf)/HepG2-Maz-ChIP-Seq(GSE31477)/Homer\n",
      "\tSkipping...\n",
      "\tJob finished - if results look good, please send beer to ..\n",
      "\n",
      "\tCleaning up tmp files...\n",
      "\n"
     ]
    }
   ],
   "source": [
    "cc.tl.call_motif(peaks_frame=cc.tl.rank_peak_groups_df(adata_cc, key = 'fisher_exact', pval_cutoff = 0.01, logfc_min = 3, group = ['Female_Brd4'])[\"names\"].str.split(\"_\", expand=True),\n",
    "                 reference =\"mm10\",save_homer = \"Homer/GBM_female\", \n",
    "                 homer_path = \"/home/juanru/miniconda3/bin/\", num_cores=12)\n",
    "cc.tl.call_motif(peaks_frame=cc.tl.rank_peak_groups_df(adata_cc, key = 'fisher_exact', pval_cutoff = 0.01, logfc_min = 3, group = ['Male_Brd4'])[\"names\"].str.split(\"_\", expand=True),\n",
    "                 reference =\"mm10\",save_homer = \"Homer/GBM_male\", \n",
    "                 homer_path = \"/home/juanru/miniconda3/bin/\", num_cores=12)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2613400d-49c6-4a57-b2c7-8b31050cb125",
   "metadata": {},
   "source": [
    "Find motifs under male peaks but not in female peaks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "432d74f3-51f0-4950-a549-ab7b2293957c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Motif Name</th>\n",
       "      <th>Consensus</th>\n",
       "      <th>P-value</th>\n",
       "      <th>Log P-value</th>\n",
       "      <th>q-value (Benjamini)</th>\n",
       "      <th># of Target Sequences with Motif(of 585)</th>\n",
       "      <th>% of Target Sequences with Motif</th>\n",
       "      <th># of Background Sequences with Motif(of 2133)</th>\n",
       "      <th>% of Background Sequences with Motif</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Nrf2(bZIP)/Lymphoblast-Nrf2-ChIP-Seq(GSE37589)...</td>\n",
       "      <td>HTGCTGAGTCAT</td>\n",
       "      <td>1.000000e-13</td>\n",
       "      <td>-30.290</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>39.0</td>\n",
       "      <td>6.67%</td>\n",
       "      <td>33.5</td>\n",
       "      <td>1.57%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>NF-E2(bZIP)/K562-NFE2-ChIP-Seq(GSE31477)/Homer</td>\n",
       "      <td>GATGACTCAGCA</td>\n",
       "      <td>1.000000e-11</td>\n",
       "      <td>-26.520</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>41.0</td>\n",
       "      <td>7.01%</td>\n",
       "      <td>41.6</td>\n",
       "      <td>1.95%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>NFE2L2(bZIP)/HepG2-NFE2L2-ChIP-Seq(Encode)/Homer</td>\n",
       "      <td>AWWWTGCTGAGTCAT</td>\n",
       "      <td>1.000000e-11</td>\n",
       "      <td>-25.480</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>48.0</td>\n",
       "      <td>8.21%</td>\n",
       "      <td>56.4</td>\n",
       "      <td>2.65%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Bach1(bZIP)/K562-Bach1-ChIP-Seq(GSE31477)/Homer</td>\n",
       "      <td>AWWNTGCTGAGTCAT</td>\n",
       "      <td>1.000000e-09</td>\n",
       "      <td>-21.840</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>39.0</td>\n",
       "      <td>6.67%</td>\n",
       "      <td>44.3</td>\n",
       "      <td>2.07%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>MafK(bZIP)/C2C12-MafK-ChIP-Seq(GSE36030)/Homer</td>\n",
       "      <td>GCTGASTCAGCA</td>\n",
       "      <td>1.000000e-09</td>\n",
       "      <td>-20.870</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>97.0</td>\n",
       "      <td>16.58%</td>\n",
       "      <td>186.9</td>\n",
       "      <td>8.76%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Ets1-distal(ETS)/CD4+-PolII-ChIP-Seq(Barski_et...</td>\n",
       "      <td>MACAGGAAGT</td>\n",
       "      <td>1.000000e-05</td>\n",
       "      <td>-13.680</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>116.0</td>\n",
       "      <td>19.83%</td>\n",
       "      <td>273.6</td>\n",
       "      <td>12.82%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Sox3(HMG)/NPC-Sox3-ChIP-Seq(GSE33059)/Homer</td>\n",
       "      <td>CCWTTGTY</td>\n",
       "      <td>1.000000e-04</td>\n",
       "      <td>-9.625</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>434.0</td>\n",
       "      <td>74.19%</td>\n",
       "      <td>1425.7</td>\n",
       "      <td>66.82%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Nkx2.2(Homeobox)/NPC-Nkx2.2-ChIP-Seq(GSE61673)...</td>\n",
       "      <td>BTBRAGTGSN</td>\n",
       "      <td>1.000000e-04</td>\n",
       "      <td>-9.612</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>419.0</td>\n",
       "      <td>71.62%</td>\n",
       "      <td>1367.5</td>\n",
       "      <td>64.09%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Bapx1(Homeobox)/VertebralCol-Bapx1-ChIP-Seq(GS...</td>\n",
       "      <td>TTRAGTGSYK</td>\n",
       "      <td>1.000000e-04</td>\n",
       "      <td>-9.553</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>467.0</td>\n",
       "      <td>79.83%</td>\n",
       "      <td>1556.7</td>\n",
       "      <td>72.96%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>RUNX1(Runt)/Jurkat-RUNX1-ChIP-Seq(GSE29180)/Homer</td>\n",
       "      <td>AAACCACARM</td>\n",
       "      <td>1.000000e-03</td>\n",
       "      <td>-8.988</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>293.0</td>\n",
       "      <td>50.09%</td>\n",
       "      <td>906.6</td>\n",
       "      <td>42.49%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>ZNF669(Zf)/HEK293-ZNF669.GFP-ChIP-Seq(GSE58341...</td>\n",
       "      <td>GARTGGTCATCGCCC</td>\n",
       "      <td>1.000000e-03</td>\n",
       "      <td>-8.215</td>\n",
       "      <td>0.0050</td>\n",
       "      <td>24.0</td>\n",
       "      <td>4.10%</td>\n",
       "      <td>39.7</td>\n",
       "      <td>1.86%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>RUNX-AML(Runt)/CD4+-PolII-ChIP-Seq(Barski_et_a...</td>\n",
       "      <td>GCTGTGGTTW</td>\n",
       "      <td>1.000000e-03</td>\n",
       "      <td>-7.530</td>\n",
       "      <td>0.0086</td>\n",
       "      <td>212.0</td>\n",
       "      <td>36.24%</td>\n",
       "      <td>637.6</td>\n",
       "      <td>29.89%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Sox10(HMG)/SciaticNerve-Sox3-ChIP-Seq(GSE35132...</td>\n",
       "      <td>CCWTTGTYYB</td>\n",
       "      <td>1.000000e-03</td>\n",
       "      <td>-7.342</td>\n",
       "      <td>0.0095</td>\n",
       "      <td>407.0</td>\n",
       "      <td>69.57%</td>\n",
       "      <td>1347.5</td>\n",
       "      <td>63.15%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Sp1(Zf)/Promoter/Homer</td>\n",
       "      <td>GGCCCCGCCCCC</td>\n",
       "      <td>1.000000e-03</td>\n",
       "      <td>-7.220</td>\n",
       "      <td>0.0104</td>\n",
       "      <td>31.0</td>\n",
       "      <td>5.30%</td>\n",
       "      <td>60.7</td>\n",
       "      <td>2.85%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>E2F3(E2F)/MEF-E2F3-ChIP-Seq(GSE71376)/Homer</td>\n",
       "      <td>BTKGGCGGGAAA</td>\n",
       "      <td>1.000000e-03</td>\n",
       "      <td>-7.074</td>\n",
       "      <td>0.0113</td>\n",
       "      <td>77.0</td>\n",
       "      <td>13.16%</td>\n",
       "      <td>195.8</td>\n",
       "      <td>9.18%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Sox7(HMG)/ESC-Sox7-ChIP-Seq(GSE133899)/Homer</td>\n",
       "      <td>VVRRAACAATGG</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-6.569</td>\n",
       "      <td>0.0162</td>\n",
       "      <td>102.0</td>\n",
       "      <td>17.44%</td>\n",
       "      <td>278.9</td>\n",
       "      <td>13.07%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Brn1(POU,Homeobox)/NPC-Brn1-ChIP-Seq(GSE35496)...</td>\n",
       "      <td>TATGCWAATBAV</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-6.345</td>\n",
       "      <td>0.0188</td>\n",
       "      <td>134.0</td>\n",
       "      <td>22.91%</td>\n",
       "      <td>385.4</td>\n",
       "      <td>18.06%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Sox4(HMG)/proB-Sox4-ChIP-Seq(GSE50066)/Homer</td>\n",
       "      <td>YCTTTGTTCC</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-6.213</td>\n",
       "      <td>0.0205</td>\n",
       "      <td>255.0</td>\n",
       "      <td>43.59%</td>\n",
       "      <td>804.0</td>\n",
       "      <td>37.68%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>ZNF317(Zf)/HEK293-ZNF317.GFP-ChIP-Seq(GSE58341...</td>\n",
       "      <td>GTCWGCTGTYYCTCT</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-6.112</td>\n",
       "      <td>0.0222</td>\n",
       "      <td>29.0</td>\n",
       "      <td>4.96%</td>\n",
       "      <td>59.0</td>\n",
       "      <td>2.77%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>OCT4-SOX2-TCF-NANOG(POU,Homeobox,HMG)/mES-Oct4...</td>\n",
       "      <td>ATTTGCATAACAATG</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-5.636</td>\n",
       "      <td>0.0341</td>\n",
       "      <td>96.0</td>\n",
       "      <td>16.41%</td>\n",
       "      <td>267.1</td>\n",
       "      <td>12.52%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Isl1(Homeobox)/Neuron-Isl1-ChIP-Seq(GSE31456)/...</td>\n",
       "      <td>CTAATKGV</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-5.578</td>\n",
       "      <td>0.0354</td>\n",
       "      <td>467.0</td>\n",
       "      <td>79.83%</td>\n",
       "      <td>1601.5</td>\n",
       "      <td>75.06%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Sox2(HMG)/mES-Sox2-ChIP-Seq(GSE11431)/Homer</td>\n",
       "      <td>BCCATTGTTC</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-5.408</td>\n",
       "      <td>0.0402</td>\n",
       "      <td>272.0</td>\n",
       "      <td>46.50%</td>\n",
       "      <td>876.6</td>\n",
       "      <td>41.09%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Egr1(Zf)/K562-Egr1-ChIP-Seq(GSE32465)/Homer</td>\n",
       "      <td>TGCGTGGGYG</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-5.339</td>\n",
       "      <td>0.0422</td>\n",
       "      <td>137.0</td>\n",
       "      <td>23.42%</td>\n",
       "      <td>406.2</td>\n",
       "      <td>19.04%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>Tbx20(T-box)/Heart-Tbx20-ChIP-Seq(GSE29636)/Homer</td>\n",
       "      <td>GGTGYTGACAGS</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-5.310</td>\n",
       "      <td>0.0426</td>\n",
       "      <td>67.0</td>\n",
       "      <td>11.45%</td>\n",
       "      <td>178.0</td>\n",
       "      <td>8.34%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>Nkx3.1(Homeobox)/LNCaP-Nkx3.1-ChIP-Seq(GSE2826...</td>\n",
       "      <td>AAGCACTTAA</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-5.277</td>\n",
       "      <td>0.0432</td>\n",
       "      <td>479.0</td>\n",
       "      <td>81.88%</td>\n",
       "      <td>1652.0</td>\n",
       "      <td>77.43%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>E2F6(E2F)/Hela-E2F6-ChIP-Seq(GSE31477)/Homer</td>\n",
       "      <td>GGCGGGAARN</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-5.256</td>\n",
       "      <td>0.0433</td>\n",
       "      <td>64.0</td>\n",
       "      <td>10.94%</td>\n",
       "      <td>168.7</td>\n",
       "      <td>7.91%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>TATA-Box(TBP)/Promoter/Homer</td>\n",
       "      <td>CCTTTTAWAGSC</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-5.201</td>\n",
       "      <td>0.0449</td>\n",
       "      <td>382.0</td>\n",
       "      <td>65.30%</td>\n",
       "      <td>1282.4</td>\n",
       "      <td>60.10%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Klf9(Zf)/GBM-Klf9-ChIP-Seq(GSE62211)/Homer</td>\n",
       "      <td>GCCACRCCCACY</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-5.137</td>\n",
       "      <td>0.0462</td>\n",
       "      <td>85.0</td>\n",
       "      <td>14.53%</td>\n",
       "      <td>236.3</td>\n",
       "      <td>11.08%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           Motif Name        Consensus  \\\n",
       "10  Nrf2(bZIP)/Lymphoblast-Nrf2-ChIP-Seq(GSE37589)...     HTGCTGAGTCAT   \n",
       "11     NF-E2(bZIP)/K562-NFE2-ChIP-Seq(GSE31477)/Homer     GATGACTCAGCA   \n",
       "12   NFE2L2(bZIP)/HepG2-NFE2L2-ChIP-Seq(Encode)/Homer  AWWWTGCTGAGTCAT   \n",
       "13    Bach1(bZIP)/K562-Bach1-ChIP-Seq(GSE31477)/Homer  AWWNTGCTGAGTCAT   \n",
       "14     MafK(bZIP)/C2C12-MafK-ChIP-Seq(GSE36030)/Homer     GCTGASTCAGCA   \n",
       "15  Ets1-distal(ETS)/CD4+-PolII-ChIP-Seq(Barski_et...       MACAGGAAGT   \n",
       "17        Sox3(HMG)/NPC-Sox3-ChIP-Seq(GSE33059)/Homer         CCWTTGTY   \n",
       "18  Nkx2.2(Homeobox)/NPC-Nkx2.2-ChIP-Seq(GSE61673)...       BTBRAGTGSN   \n",
       "19  Bapx1(Homeobox)/VertebralCol-Bapx1-ChIP-Seq(GS...       TTRAGTGSYK   \n",
       "20  RUNX1(Runt)/Jurkat-RUNX1-ChIP-Seq(GSE29180)/Homer       AAACCACARM   \n",
       "23  ZNF669(Zf)/HEK293-ZNF669.GFP-ChIP-Seq(GSE58341...  GARTGGTCATCGCCC   \n",
       "27  RUNX-AML(Runt)/CD4+-PolII-ChIP-Seq(Barski_et_a...       GCTGTGGTTW   \n",
       "29  Sox10(HMG)/SciaticNerve-Sox3-ChIP-Seq(GSE35132...       CCWTTGTYYB   \n",
       "30                             Sp1(Zf)/Promoter/Homer     GGCCCCGCCCCC   \n",
       "32        E2F3(E2F)/MEF-E2F3-ChIP-Seq(GSE71376)/Homer     BTKGGCGGGAAA   \n",
       "37       Sox7(HMG)/ESC-Sox7-ChIP-Seq(GSE133899)/Homer     VVRRAACAATGG   \n",
       "40  Brn1(POU,Homeobox)/NPC-Brn1-ChIP-Seq(GSE35496)...     TATGCWAATBAV   \n",
       "42       Sox4(HMG)/proB-Sox4-ChIP-Seq(GSE50066)/Homer       YCTTTGTTCC   \n",
       "43  ZNF317(Zf)/HEK293-ZNF317.GFP-ChIP-Seq(GSE58341...  GTCWGCTGTYYCTCT   \n",
       "45  OCT4-SOX2-TCF-NANOG(POU,Homeobox,HMG)/mES-Oct4...  ATTTGCATAACAATG   \n",
       "46  Isl1(Homeobox)/Neuron-Isl1-ChIP-Seq(GSE31456)/...         CTAATKGV   \n",
       "48        Sox2(HMG)/mES-Sox2-ChIP-Seq(GSE11431)/Homer       BCCATTGTTC   \n",
       "49        Egr1(Zf)/K562-Egr1-ChIP-Seq(GSE32465)/Homer       TGCGTGGGYG   \n",
       "50  Tbx20(T-box)/Heart-Tbx20-ChIP-Seq(GSE29636)/Homer     GGTGYTGACAGS   \n",
       "51  Nkx3.1(Homeobox)/LNCaP-Nkx3.1-ChIP-Seq(GSE2826...       AAGCACTTAA   \n",
       "52       E2F6(E2F)/Hela-E2F6-ChIP-Seq(GSE31477)/Homer       GGCGGGAARN   \n",
       "53                       TATA-Box(TBP)/Promoter/Homer     CCTTTTAWAGSC   \n",
       "55         Klf9(Zf)/GBM-Klf9-ChIP-Seq(GSE62211)/Homer     GCCACRCCCACY   \n",
       "\n",
       "         P-value  Log P-value  q-value (Benjamini)  \\\n",
       "10  1.000000e-13      -30.290               0.0000   \n",
       "11  1.000000e-11      -26.520               0.0000   \n",
       "12  1.000000e-11      -25.480               0.0000   \n",
       "13  1.000000e-09      -21.840               0.0000   \n",
       "14  1.000000e-09      -20.870               0.0000   \n",
       "15  1.000000e-05      -13.680               0.0000   \n",
       "17  1.000000e-04       -9.625               0.0016   \n",
       "18  1.000000e-04       -9.612               0.0016   \n",
       "19  1.000000e-04       -9.553               0.0016   \n",
       "20  1.000000e-03       -8.988               0.0026   \n",
       "23  1.000000e-03       -8.215               0.0050   \n",
       "27  1.000000e-03       -7.530               0.0086   \n",
       "29  1.000000e-03       -7.342               0.0095   \n",
       "30  1.000000e-03       -7.220               0.0104   \n",
       "32  1.000000e-03       -7.074               0.0113   \n",
       "37  1.000000e-02       -6.569               0.0162   \n",
       "40  1.000000e-02       -6.345               0.0188   \n",
       "42  1.000000e-02       -6.213               0.0205   \n",
       "43  1.000000e-02       -6.112               0.0222   \n",
       "45  1.000000e-02       -5.636               0.0341   \n",
       "46  1.000000e-02       -5.578               0.0354   \n",
       "48  1.000000e-02       -5.408               0.0402   \n",
       "49  1.000000e-02       -5.339               0.0422   \n",
       "50  1.000000e-02       -5.310               0.0426   \n",
       "51  1.000000e-02       -5.277               0.0432   \n",
       "52  1.000000e-02       -5.256               0.0433   \n",
       "53  1.000000e-02       -5.201               0.0449   \n",
       "55  1.000000e-02       -5.137               0.0462   \n",
       "\n",
       "    # of Target Sequences with Motif(of 585) % of Target Sequences with Motif  \\\n",
       "10                                      39.0                            6.67%   \n",
       "11                                      41.0                            7.01%   \n",
       "12                                      48.0                            8.21%   \n",
       "13                                      39.0                            6.67%   \n",
       "14                                      97.0                           16.58%   \n",
       "15                                     116.0                           19.83%   \n",
       "17                                     434.0                           74.19%   \n",
       "18                                     419.0                           71.62%   \n",
       "19                                     467.0                           79.83%   \n",
       "20                                     293.0                           50.09%   \n",
       "23                                      24.0                            4.10%   \n",
       "27                                     212.0                           36.24%   \n",
       "29                                     407.0                           69.57%   \n",
       "30                                      31.0                            5.30%   \n",
       "32                                      77.0                           13.16%   \n",
       "37                                     102.0                           17.44%   \n",
       "40                                     134.0                           22.91%   \n",
       "42                                     255.0                           43.59%   \n",
       "43                                      29.0                            4.96%   \n",
       "45                                      96.0                           16.41%   \n",
       "46                                     467.0                           79.83%   \n",
       "48                                     272.0                           46.50%   \n",
       "49                                     137.0                           23.42%   \n",
       "50                                      67.0                           11.45%   \n",
       "51                                     479.0                           81.88%   \n",
       "52                                      64.0                           10.94%   \n",
       "53                                     382.0                           65.30%   \n",
       "55                                      85.0                           14.53%   \n",
       "\n",
       "    # of Background Sequences with Motif(of 2133)  \\\n",
       "10                                           33.5   \n",
       "11                                           41.6   \n",
       "12                                           56.4   \n",
       "13                                           44.3   \n",
       "14                                          186.9   \n",
       "15                                          273.6   \n",
       "17                                         1425.7   \n",
       "18                                         1367.5   \n",
       "19                                         1556.7   \n",
       "20                                          906.6   \n",
       "23                                           39.7   \n",
       "27                                          637.6   \n",
       "29                                         1347.5   \n",
       "30                                           60.7   \n",
       "32                                          195.8   \n",
       "37                                          278.9   \n",
       "40                                          385.4   \n",
       "42                                          804.0   \n",
       "43                                           59.0   \n",
       "45                                          267.1   \n",
       "46                                         1601.5   \n",
       "48                                          876.6   \n",
       "49                                          406.2   \n",
       "50                                          178.0   \n",
       "51                                         1652.0   \n",
       "52                                          168.7   \n",
       "53                                         1282.4   \n",
       "55                                          236.3   \n",
       "\n",
       "   % of Background Sequences with Motif  \n",
       "10                                1.57%  \n",
       "11                                1.95%  \n",
       "12                                2.65%  \n",
       "13                                2.07%  \n",
       "14                                8.76%  \n",
       "15                               12.82%  \n",
       "17                               66.82%  \n",
       "18                               64.09%  \n",
       "19                               72.96%  \n",
       "20                               42.49%  \n",
       "23                                1.86%  \n",
       "27                               29.89%  \n",
       "29                               63.15%  \n",
       "30                                2.85%  \n",
       "32                                9.18%  \n",
       "37                               13.07%  \n",
       "40                               18.06%  \n",
       "42                               37.68%  \n",
       "43                                2.77%  \n",
       "45                               12.52%  \n",
       "46                               75.06%  \n",
       "48                               41.09%  \n",
       "49                               19.04%  \n",
       "50                                8.34%  \n",
       "51                               77.43%  \n",
       "52                                7.91%  \n",
       "53                               60.10%  \n",
       "55                               11.08%  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cc.tl.compare_motif(\"Homer/GBM_male\", \"Homer/GBM_female\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e21a5e5-5e50-4d50-84e9-03141df8a5df",
   "metadata": {},
   "source": [
    "Find motifs in female but not in male."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ec234c26-a97d-4943-9d2c-946282692ca1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Motif Name</th>\n",
       "      <th>Consensus</th>\n",
       "      <th>P-value</th>\n",
       "      <th>Log P-value</th>\n",
       "      <th>q-value (Benjamini)</th>\n",
       "      <th># of Target Sequences with Motif(of 1009)</th>\n",
       "      <th>% of Target Sequences with Motif</th>\n",
       "      <th># of Background Sequences with Motif(of 2327)</th>\n",
       "      <th>% of Background Sequences with Motif</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Atf4(bZIP)/MEF-Atf4-ChIP-Seq(GSE35681)/Homer</td>\n",
       "      <td>MTGATGCAAT</td>\n",
       "      <td>1.000000e-14</td>\n",
       "      <td>-33.810</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>228.0</td>\n",
       "      <td>22.60%</td>\n",
       "      <td>313.9</td>\n",
       "      <td>13.49%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Chop(bZIP)/MEF-Chop-ChIP-Seq(GSE35681)/Homer</td>\n",
       "      <td>ATTGCATCAT</td>\n",
       "      <td>1.000000e-14</td>\n",
       "      <td>-32.890</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>197.0</td>\n",
       "      <td>19.52%</td>\n",
       "      <td>259.5</td>\n",
       "      <td>11.15%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>IRF8(IRF)/BMDM-IRF8-ChIP-Seq(GSE77884)/Homer</td>\n",
       "      <td>GRAASTGAAAST</td>\n",
       "      <td>1.000000e-12</td>\n",
       "      <td>-28.550</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>255.0</td>\n",
       "      <td>25.27%</td>\n",
       "      <td>381.5</td>\n",
       "      <td>16.40%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>EBF1(EBF)/Near-E2A-ChIP-Seq(GSE21512)/Homer</td>\n",
       "      <td>GTCCCCWGGGGA</td>\n",
       "      <td>1.000000e-11</td>\n",
       "      <td>-27.250</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>310.0</td>\n",
       "      <td>30.72%</td>\n",
       "      <td>495.0</td>\n",
       "      <td>21.27%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Zic3(Zf)/mES-Zic3-ChIP-Seq(GSE37889)/Homer</td>\n",
       "      <td>GGCCYCCTGCTGDGH</td>\n",
       "      <td>1.000000e-11</td>\n",
       "      <td>-25.440</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>189.0</td>\n",
       "      <td>18.73%</td>\n",
       "      <td>266.5</td>\n",
       "      <td>11.45%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>SPDEF(ETS)/VCaP-SPDEF-ChIP-Seq(SRA014231)/Homer</td>\n",
       "      <td>ASWTCCTGBT</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-4.786</td>\n",
       "      <td>0.0299</td>\n",
       "      <td>420.0</td>\n",
       "      <td>41.63%</td>\n",
       "      <td>882.4</td>\n",
       "      <td>37.92%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>Srebp2(bHLH)/HepG2-Srebp2-ChIP-Seq(GSE31477)/H...</td>\n",
       "      <td>CGGTCACSCCAC</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-4.760</td>\n",
       "      <td>0.0304</td>\n",
       "      <td>45.0</td>\n",
       "      <td>4.46%</td>\n",
       "      <td>71.8</td>\n",
       "      <td>3.08%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>ZNF519(Zf)/HEK293-ZNF519.GFP-ChIP-Seq(GSE58341...</td>\n",
       "      <td>GAGSCCGAGC</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-4.720</td>\n",
       "      <td>0.0314</td>\n",
       "      <td>37.0</td>\n",
       "      <td>3.67%</td>\n",
       "      <td>56.1</td>\n",
       "      <td>2.41%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>AP-2alpha(AP2)/Hela-AP2alpha-ChIP-Seq(GSE31477...</td>\n",
       "      <td>ATGCCCTGAGGC</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-4.695</td>\n",
       "      <td>0.0319</td>\n",
       "      <td>167.0</td>\n",
       "      <td>16.55%</td>\n",
       "      <td>323.9</td>\n",
       "      <td>13.92%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>Atf7(bZIP)/3T3L1-Atf7-ChIP-Seq(GSE56872)/Homer</td>\n",
       "      <td>NGRTGACGTCAY</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>-4.676</td>\n",
       "      <td>0.0323</td>\n",
       "      <td>192.0</td>\n",
       "      <td>19.03%</td>\n",
       "      <td>377.5</td>\n",
       "      <td>16.22%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>98 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            Motif Name        Consensus  \\\n",
       "0         Atf4(bZIP)/MEF-Atf4-ChIP-Seq(GSE35681)/Homer       MTGATGCAAT   \n",
       "1         Chop(bZIP)/MEF-Chop-ChIP-Seq(GSE35681)/Homer       ATTGCATCAT   \n",
       "2         IRF8(IRF)/BMDM-IRF8-ChIP-Seq(GSE77884)/Homer     GRAASTGAAAST   \n",
       "5          EBF1(EBF)/Near-E2A-ChIP-Seq(GSE21512)/Homer     GTCCCCWGGGGA   \n",
       "8           Zic3(Zf)/mES-Zic3-ChIP-Seq(GSE37889)/Homer  GGCCYCCTGCTGDGH   \n",
       "..                                                 ...              ...   \n",
       "122    SPDEF(ETS)/VCaP-SPDEF-ChIP-Seq(SRA014231)/Homer       ASWTCCTGBT   \n",
       "123  Srebp2(bHLH)/HepG2-Srebp2-ChIP-Seq(GSE31477)/H...     CGGTCACSCCAC   \n",
       "124  ZNF519(Zf)/HEK293-ZNF519.GFP-ChIP-Seq(GSE58341...       GAGSCCGAGC   \n",
       "125  AP-2alpha(AP2)/Hela-AP2alpha-ChIP-Seq(GSE31477...     ATGCCCTGAGGC   \n",
       "126     Atf7(bZIP)/3T3L1-Atf7-ChIP-Seq(GSE56872)/Homer     NGRTGACGTCAY   \n",
       "\n",
       "          P-value  Log P-value  q-value (Benjamini)  \\\n",
       "0    1.000000e-14      -33.810               0.0000   \n",
       "1    1.000000e-14      -32.890               0.0000   \n",
       "2    1.000000e-12      -28.550               0.0000   \n",
       "5    1.000000e-11      -27.250               0.0000   \n",
       "8    1.000000e-11      -25.440               0.0000   \n",
       "..            ...          ...                  ...   \n",
       "122  1.000000e-02       -4.786               0.0299   \n",
       "123  1.000000e-02       -4.760               0.0304   \n",
       "124  1.000000e-02       -4.720               0.0314   \n",
       "125  1.000000e-02       -4.695               0.0319   \n",
       "126  1.000000e-02       -4.676               0.0323   \n",
       "\n",
       "     # of Target Sequences with Motif(of 1009)  \\\n",
       "0                                        228.0   \n",
       "1                                        197.0   \n",
       "2                                        255.0   \n",
       "5                                        310.0   \n",
       "8                                        189.0   \n",
       "..                                         ...   \n",
       "122                                      420.0   \n",
       "123                                       45.0   \n",
       "124                                       37.0   \n",
       "125                                      167.0   \n",
       "126                                      192.0   \n",
       "\n",
       "    % of Target Sequences with Motif  \\\n",
       "0                             22.60%   \n",
       "1                             19.52%   \n",
       "2                             25.27%   \n",
       "5                             30.72%   \n",
       "8                             18.73%   \n",
       "..                               ...   \n",
       "122                           41.63%   \n",
       "123                            4.46%   \n",
       "124                            3.67%   \n",
       "125                           16.55%   \n",
       "126                           19.03%   \n",
       "\n",
       "     # of Background Sequences with Motif(of 2327)  \\\n",
       "0                                            313.9   \n",
       "1                                            259.5   \n",
       "2                                            381.5   \n",
       "5                                            495.0   \n",
       "8                                            266.5   \n",
       "..                                             ...   \n",
       "122                                          882.4   \n",
       "123                                           71.8   \n",
       "124                                           56.1   \n",
       "125                                          323.9   \n",
       "126                                          377.5   \n",
       "\n",
       "    % of Background Sequences with Motif  \n",
       "0                                 13.49%  \n",
       "1                                 11.15%  \n",
       "2                                 16.40%  \n",
       "5                                 21.27%  \n",
       "8                                 11.45%  \n",
       "..                                   ...  \n",
       "122                               37.92%  \n",
       "123                                3.08%  \n",
       "124                                2.41%  \n",
       "125                               13.92%  \n",
       "126                               16.22%  \n",
       "\n",
       "[98 rows x 9 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cc.tl.compare_motif(\"Homer/GBM_female\", \"Homer/GBM_male\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58d3d7a3-a09f-4e5e-aaf8-5686d6bc4876",
   "metadata": {},
   "source": [
    "Next, we want to identify differentially bound peaks whose nearby genes are differentially expressed between males and females. To do so, we must first read in the bulk RNA-seq data. Note that this RNA-seq data is normalized by [RPKM](https://wiki.arrayserver.com/wiki/index.php?title=RPKM)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "df6850dd-8e08-4326-8bfc-217fc3978483",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sample.f6_dmso_3</th>\n",
       "      <th>sample.f6_dmso_2</th>\n",
       "      <th>sample.f6_dmso_1</th>\n",
       "      <th>sample.m6_dmso_3</th>\n",
       "      <th>sample.m6_dmso_2</th>\n",
       "      <th>sample.m6_dmso_1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mt-Tf</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.639272</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.156308</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.687531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mt-Rnr1</th>\n",
       "      <td>127.907281</td>\n",
       "      <td>184.396768</td>\n",
       "      <td>172.544723</td>\n",
       "      <td>130.417054</td>\n",
       "      <td>192.566581</td>\n",
       "      <td>114.212201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mt-Tv</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.761150</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.510777</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mt-Rnr2</th>\n",
       "      <td>247.267306</td>\n",
       "      <td>527.855824</td>\n",
       "      <td>324.345998</td>\n",
       "      <td>675.031187</td>\n",
       "      <td>684.376279</td>\n",
       "      <td>418.345603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mt-Tl1</th>\n",
       "      <td>44.418710</td>\n",
       "      <td>117.660098</td>\n",
       "      <td>70.481211</td>\n",
       "      <td>167.217607</td>\n",
       "      <td>115.129081</td>\n",
       "      <td>127.789076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gm16897</th>\n",
       "      <td>0.281553</td>\n",
       "      <td>0.349020</td>\n",
       "      <td>0.463442</td>\n",
       "      <td>0.078913</td>\n",
       "      <td>0.070742</td>\n",
       "      <td>0.112610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A330023F24Rik</th>\n",
       "      <td>0.118678</td>\n",
       "      <td>0.055749</td>\n",
       "      <td>0.058441</td>\n",
       "      <td>0.029411</td>\n",
       "      <td>0.018833</td>\n",
       "      <td>0.049965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cd46</th>\n",
       "      <td>0.127930</td>\n",
       "      <td>0.095151</td>\n",
       "      <td>0.075997</td>\n",
       "      <td>0.061467</td>\n",
       "      <td>0.055103</td>\n",
       "      <td>0.087715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cr1l</th>\n",
       "      <td>9.993119</td>\n",
       "      <td>14.027801</td>\n",
       "      <td>13.717564</td>\n",
       "      <td>13.586101</td>\n",
       "      <td>13.240219</td>\n",
       "      <td>11.089902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cr2</th>\n",
       "      <td>0.018832</td>\n",
       "      <td>0.056028</td>\n",
       "      <td>0.019578</td>\n",
       "      <td>0.012668</td>\n",
       "      <td>0.017034</td>\n",
       "      <td>0.015064</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21430 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               sample.f6_dmso_3  sample.f6_dmso_2  sample.f6_dmso_1  \\\n",
       "mt-Tf                  0.000000          0.639272          0.000000   \n",
       "mt-Rnr1              127.907281        184.396768        172.544723   \n",
       "mt-Tv                  0.000000          0.000000          1.761150   \n",
       "mt-Rnr2              247.267306        527.855824        324.345998   \n",
       "mt-Tl1                44.418710        117.660098         70.481211   \n",
       "...                         ...               ...               ...   \n",
       "Gm16897                0.281553          0.349020          0.463442   \n",
       "A330023F24Rik          0.118678          0.055749          0.058441   \n",
       "Cd46                   0.127930          0.095151          0.075997   \n",
       "Cr1l                   9.993119         14.027801         13.717564   \n",
       "Cr2                    0.018832          0.056028          0.019578   \n",
       "\n",
       "               sample.m6_dmso_3  sample.m6_dmso_2  sample.m6_dmso_1  \n",
       "mt-Tf                  1.156308          0.000000          0.687531  \n",
       "mt-Rnr1              130.417054        192.566581        114.212201  \n",
       "mt-Tv                  0.000000          0.510777          0.000000  \n",
       "mt-Rnr2              675.031187        684.376279        418.345603  \n",
       "mt-Tl1               167.217607        115.129081        127.789076  \n",
       "...                         ...               ...               ...  \n",
       "Gm16897                0.078913          0.070742          0.112610  \n",
       "A330023F24Rik          0.029411          0.018833          0.049965  \n",
       "Cd46                   0.061467          0.055103          0.087715  \n",
       "Cr1l                  13.586101         13.240219         11.089902  \n",
       "Cr2                    0.012668          0.017034          0.015064  \n",
       "\n",
       "[21430 rows x 6 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rna =  cc.datasets.mouse_brd4_data(data = \"RNA\")\n",
    "rna"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9885e882-654d-4f01-bace-4528100eec5c",
   "metadata": {},
   "source": [
    "We now plot the heatmap for calling cards data and gene expression data. \n",
    "\n",
    "The top lines are the relative Brd4 binding for each of the two groups. The bottom lines are the gene expressions of the top two nearest genes in the 3 RNA-seq replicates for males and females; each gene shown separately. \n",
    "\n",
    "We can see a relationship between Brd4 binding and the expression of nearby genes. Genes that are strongly bound in females tend to be expressed in females and expressed at lower levels in males and vice versa. The effect is much more muted for the 2nd nearest gene to the peak. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "29add18c-b154-45c5-b214-645ea7f6ed7c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Please make sure that the samples in adata_cc and rna are in the same order.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/juanru/Desktop/pycallingcards/pycallingcards/pycallingcards/plotting/_heatmap_ccrna.py:193: RuntimeWarning: invalid value encountered in true_divide\n",
      "  data[groupnumber:secondnum, :]\n",
      "/home/juanru/Desktop/pycallingcards/pycallingcards/pycallingcards/plotting/_heatmap_ccrna.py:195: RuntimeWarning: invalid value encountered in true_divide\n",
      "  data[secondnum:, :]\n"
     ]
    },
    {
     "data": {
      "image/png": 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r1izw18i9e/dWnTp1CpTVoUMH3X333bLb7R7Ls/9VWrdurSeeeEIWi8WdFhERoYEDB0pSgeXcFyxYIEl67LHHPP4a3GKxaOzYsQoLCytzDOe7/by9vfXqq696nPs8H330kSRp1KhRat68uTvdy8tL48ePV+3atQvsk5GRIavVqoYNG3q0SZ769et7lFWS5s2bF7pySEhIiCZMmCCp+Oto9OjR7r/mzzN8+HAFBQXp+PHjOn36tDt969at2r17t6pVq6YXX3xRvr6+7m3h4eF69tlnSx13Sex2u/sxB9u3b1erVq302GOPlbifn5+fRo0aJUmaNm2anE5nqepbs2aNTp8+rVq1aumqq65yp+f9xf2PP/7oXoWmMk2YMEFNmzZ1v7ZYLHryyScl5T7+wG63l7qsxYsXKz09Xa1bt9YjjzziXqVGktq2basRI0ZIkubOnVvo/tWrV9cLL7xQ5KocUu64PWLECI+y77zzTlWvXl2xsbHq3r27brrpJo99HnnkEUnS5s2bCxzP+R7bPvzwQ0nSXXfdpZ49e3psu+2229SnTx/Z7Xb32JXftddeqzvuuMMjrXv37rriiivkdDq1YcOGSosVAAAAAM4HHg8BAAAAoEqNHz9e48eP90izWCx666233D9C59m3b5/i4+PVqFEjtWnTptDyunTpIkkFnsVenJycHK1Zs0a7d+9WUlKS7Ha7DMNw/zh47NixshxSsRo1aqTLL79cmzdv1i+//OIxOWHp0qWy2+26/vrrVb16dXf6ypUrJeX+UOXlVfBjnNlsVufOnXXw4EFt37690EkY+a1evVqSdPvtt5cp/jNnzmjlypU6ePCg0tLS5HA4JOUu6S5VblsVpU+fPh4/VubJ+5E9Li7OnRYbG6uoqChJ8mjrPD4+PrruuuuK/HGwKOe7/Vq1aqWGDRsWSI+Li9OJEyckqcD1Ikm+vr7q37+/Pv74Y4/00NBQ1a9fXwcOHNDkyZN16623qkWLFmU6lvycTqc2bdqkbdu2KSEhQTabTYZhyDCMYo9Nyj2n+fn4+Khhw4bat2+f4uLiVK9ePUm5P6JLuUv0F7YUf9++fRUUFKT09PRyHcemTZsUGRlZaIzTp08v9sf0cw0aNEjz58/XoUOH9NVXXxW51P+5vvjiC0nS//3f/3lc63mTqw4ePKgffvhBt912WymPpmReXl4ejzfIU7t2bYWEhCg1NVUpKSmFTn4pTN75yf/onDy33nqr3njjDR0/flxxcXEFJg11795dQUFBxdbRq1evAmOAl5eX6tevr5SUFPXu3bvAPjVq1FD16tWVkpJS6PGcr7HN4XBo27Ztkopvo99//73IR50Udr1IuWPg6tWrFR8fXymxAgAAAMD5wqQFAAAAAFXq3GeiJycna8uWLcrMzNRLL72kJk2aqF27du68eT8+nzx5stAfFc+VnJxcqvp37NihJ598UjExMUXmyXuWfWW55ZZbtHnzZi1ZssTjh/QlS5ZIyv2x81x5x/3uu+/q3XffLbbs0h533vEW9lf2RVm8eLEmTZqkrKysIvP8FX8Fnl/ej9f55a1CkJOT406LjY2VlPuDZUBAQKH71a9fv8wxnO/2KyrG0hxfgwYNCk1/8803NXr0aM2bN0/z5s1T9erV1a5dO/Xs2VMDBw5UaGhocYfj4fjx4xo1apQOHTpUZJ7irqPw8PBC0/PO6bmrkuQdc1FtYjKZVL9+ff3xxx8lxl2YWrVquX/Ez87O1h9//KHjx4/r999/17vvvutegaUkeasVjBw5UjNmzNCNN97osSpEfsnJyVq+fLmkP1dkOdctt9yiSZMm6csvv6zUSQu1a9eWt7d3odsCAwOVmppaYFWY4uRNGiqq3wUHB7snDxQ2aaE012NRY0DeNVDc9pSUlALHcz7HtnPrL6qN8iYonTsB61wljYFlOV8AAAAAcCFg0gIAAACAKnXbbbd5/Eifnp6ukSNHauPGjXriiSf0/fffy9/fX5Lcf7Fdu3ZtXXHFFcWWW9hfYOeXnZ2tkSNHKjExUYMGDdKdd96pxo0bKzAwUBaLRceOHVP//v0rcHSF69+/v1599VWtX79esbGxqlu3rvbu3asDBw4oLCyswLG5XC5JUqdOndSoUaNiy27ZsmWlxytJe/bs0QsvvCCLxaIxY8bo6quvVr169eTv7y+TyaTPPvtML7zwgvsc/ZXM5rI/6bCwlRlKs62yVLT9/Pz8Kj2mzp07a/ny5VqxYoU2b96s7du3a82aNVq1apWmT5+umTNnqnv37qUqa/To0Tp06JD69Omjhx56SM2bN1dgYKC8vb2Vk5Pj8ZiXwpTnnP5VmjVrpsmTJ3ukffzxx3rttdf03//+V126dCn0L/kLc80116hDhw7avn27Pv74Yz300ENF5v3mm29kt9vl5eXlfqTGufJ+UN++fbuOHDlSpsd3FOdCanupdH29pJjLckwX0thWWhfaOQMAAACAimLSAgAAAIALSlBQkN555x1df/31OnXqlObNm6dHH31UklS3bl1Juc88z/+jYnls3rxZiYmJat26tSZNmlRge96y+5XN399f119/vb744gt99dVXeuSRR/TVV19Jyl0uPP8PUnl/Vdu3b189+OCDlRJDvXr1dOzYMR09etS90kVxli1bJsMwNGTIED388MMFtuctoX6hyfsr7uTkZGVlZalatWoF8pw6darM5V4o7Zd3fGfOnFFmZmahqy0Ud3x+fn7q37+/e3JOcnKy3nnnHX322Wd67rnn9Pvvv5cYw5EjR3TgwAHVrFlT7733XoFHmFT2dZR3zMUdV3Erp5THPffco127dmnp0qWaNGmSevbsWeijWgozZswY3X333Zo9e7YGDx5cZL68R0Oc+/iA4vI+++yzpT+A8ygsLExHjx51rxCTX3p6ulJSUtx5q9r5HtuqV68uHx8f5eTkKCoqSpdcckmBPHltdyG0DwAAAACcD0zNBgAAAHDBCQ0N1SOPPCJJ+vDDD5WWliZJatu2rWrUqKHDhw8Xuwx9aaWmpkoqeqntpUuXFrlv3nLqec89L6u85d+//vpr5eTk6Ntvv5VU+DPOe/XqJenPH9cqQ97y94sXLy5V/ry2KmwZf5vNpp9//rlS4qps9erVcy83//333xfYnpOTU67YL5T2q1u3rnsp+e+++67A9pycHC1btqzU5YWGhroffxATE+OOuzh5eerUqVPoD/nFXUfl0aVLF0nS6tWr3T9+n+u3335zjxmVacyYMfLz89OxY8f0zTfflHq/zp07q0+fPkpNTdV//vOfQvNs375dhw8flo+PjzZv3qwDBw4U+m/27NmSctu0vGPPXy3v/Hz99deFbv/yyy8lSU2aNLkgfpQv77VZ3vcALy8vderUSZLck9Xyy2ujrl27lqlsAAAAALhYMWkBAAAAwAXprrvuUnh4uNLT0/Xhhx9Kyv2RaNSoUTIMQ6NGjdKWLVsK7Od0OrV+/Xrt2LGjxDrylldfv369Dh8+7LHts88+0w8//FDkvnk/tuXfr7Q6duyopk2b6vjx43rrrbeUkpKiTp06qUmTJgXy9u3bV23bttWuXbs0fvx4JScnF8iTmpqqRYsWlfoHtPvvv18BAQFavny5pk2bJrvd7rE9KSnJo33z2urrr79WRkaGO91ms+mll15SdHR0qeqtCkOHDpUkTZ8+XceOHXOnu1wuTZ06VadPny5zmRdS+917772SpBkzZujIkSPudKfTqTfeeEPx8fEF9jl16pQ+//xzj1jyLF++XJIUEhKiwMDAEutv0qSJLBaLDh48qI0bNxYoa/78+WU5nBJ17txZrVu3VlZWll555RXl5OS4t50+fVpvvvlmpdaXJywsTEOGDJEkffDBB2X6sfqpp56S2WzWwoUL3Y97OVfeKgt9+/ZVcHBwkeVcccUVql27thITE7VixYqyHcB5MnjwYAUGBmrv3r2aNWuWx0Srffv26YMPPpCkSls1pqLKe23mrfxz4sSJAtd/Se6//35J0qJFi7R+/XqPbUuWLNHy5cvl7e3tHrsAAAAA4O+Ox0MAAAAAuCD5+Pho1KhReu6557RgwQLdd999ql69uoYMGaKYmBjNnTtXd999t1q2bKlGjRrJz89PCQkJ+uOPP5SWlqaXXnpJ7du3L7aOSy+9VH379tVvv/2mm266SV27dlVISIj279+vY8eOafjw4Zo1a1ah+1577bX68MMPdd9996lbt27uZfnHjBmjGjVqlOoYBw0apClTpmjBggWS/lx9IT+z2ayZM2dq+PDh+uqrr/TTTz8pMjJS4eHhstvtioqK0sGDB+V0OjVo0KBSLVsfHh6u6dOna/To0Zo1a5a++OILtW/fXl5eXoqJidH+/fs1YMAAde7c2R3rggULtG/fPvXt21edO3eWxWLRli1bZLVaNXToUPdxXGjuuecerV27VqtWrdLAgQPVtWtXBQcHa/fu3YqPj9ddd92lTz75xP2X06VxIbXf3XffrbVr1+r333/X//3f/7n78c6dO5WQkKA777xTixYt8tgnLS1NEyZM0Msvv6xLLrlEDRo0kJT7A+y+fftkMpk0duxYWSyWEusPDQ3V3Xff7b5OO3furDp16ujYsWPau3evHnnkEfcP1ZXlzTff1D333KPvv/9emzdvVqdOnWS1WrVhwwZFRkaqQ4cO2r59e6XWKUnDhg3T4sWLFRUVpSVLlhT7uIdzRURE6KabbtKSJUsKbMvMzHRPkCpspZVzWSwWDRgwQPPmzdMXX3yha665puwH8RerVauW3n77bT3++OOaNm2avvnmG1166aVKSkrS5s2b5XA4NGjQoFK33V+tvNdmeHi42rRpoz179ujGG29UmzZt5Ovrqxo1amjMmDHF1tm7d2/3dXH//ferY8eO7kfO7N27VxaLRS+99JJatmz5Vx02AAAAAFxQWGkBAAAAwAXrpptuUosWLZSZmam5c+e605955hktWrRIN954o7KysrR69WqtWLFC8fH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x0j0OSlKQJUjb03a5x5Rqlmpat/obpW85oOBWTXWuGbd9qlhbnMJ868jf7KdOIe21KXq9rE6r9mccVLojQ/V8w7Ru9TdKyEnM7W/ZUbIbdgWcjc/P7Of+LJSYk6xqFn999N0+GZlWdzv6N67u7qNmk0mbYjbk9uPWdc9ed77umBr5NVDUH7vd+b1Nud/jhPpUV5hvbXcbugyXXHK5P0/kvW/njWEZZ+/3aniHKNWRJn9fL2V/sVv1fMOUkJPors9isrivsfDeXRRtjVFiTrKsLpv7Pc9m5I4vix1LVS20hgL9grU5bpO8zV7u+9C8ewDz2fHQYrJoS/JWJeec0bH4Q2c/C9s08vVr3fVVs/grOSlWknTmdHTu9xQmk1IT4+U4ez6tqWln28hHAZYA+UTWzY1x/S655FI1i79q+YQqyCtQMdbTcsalqrp3SO73BvY07Y3fJZdh6GDKQV0W3EZHs47L3KOB+/hNPl6536vILFdSug7E7tVgr4Hu7YZcf35mtJi08r3Z7m2JOclyGYZirKflb8k9h6cmrpKv2Ueh3jXc50bK/X5Pko5ln3Df11ldVh3MPFLgM7BJZvmafZV+9rP6H/s26ue7n8+99zo7DuxM2537+V6u3HZyWZXuyFC7oNZqUa2ZAiwBirbGKMQrWOlnx7HufW9WrC1O8Rm5n1NT4v4cJ7Oc2UrMyf1+MiEnUTW8QxSXHa+W4SEK8Q6Syd9HR7OOKycuUyY/b2Um5N4T5fXTGOtpxaed1pYz22Rz5SjAq5pi9+zV9v2rFGAJkGP5cflbfOVn8dPaX79UbZ9airGeVlP/xtp4eKWW74hRYP262p62S1HWaKWdvbcI8gpUnC1BWc5sNfALl92wK86W+/1q3n1cm6BLtebbT2Vz5ehw1lEFeQXKueKETh7YLSn3+1aXXIqyRutk8jFV96quxv4NdfK5T3U8+4QuC26jlbP/q1RHmrKd2UrIjtdgr4HKcGa66zLLLB+zj2L37dO6Dd9Jyv3+4Gj6Ucli8uj7gZYA+Zp9JEnpsXFq7N9QQV5BOpEdJbPJrNh9ud+Trd+2TKs/WaDdaXu12LFUknRZcBtJUs++t+hMaoKMHIdu/nWawv3q5r7vH/hdkhRnS5Cv2UcOw65d6XuVcyT3OtqVvlfTb/qfoqzROpEdJdvOE/p8de694IHMQ9qZtkcDNoyTkWKT1WXVlbcN0bHsEwrzrSNnQpq7PwVdljs2HUo7pBjraWU6M2VbeUzR1hj9cXy7u9/EWE9r37Et2p62SzYjR6s/WeDeNthroLsdrE6blu+IUYYzU5kxcTqRHaWdabvVOaSDMpyZWr3oY53IjlKoT3Vt2PebUlafkM2Vo1CfGpLTkMVkUTWLv3al5V6fB3ZvlLfJWzV9QuXdvJbq+YZp+k3/c38mSMxJlm9goDuOtb8vUaojTbUjWp4d82xSdJq8Td6ydKmvWGtuPz6YeUSStPHwSu1K36uknNzPKIFeAe6xdX/qH3LEp7rHkShrtJJtyVrz/WeKs8XL1+yjDsHtlLMnWtG7d+nk2fc+p5H7XYXTcOrKGc9Kyh0no60xkqQ1337qvv4WO5YqxCtYcuSeDz+zn6Ks0arrG6bOoZ10Mv6IDmce1f+ufExPBY5QkCVIAaH+2vPxV0qxp6qWT6h8zT65fcCW+zkwr1829m/oPkerv/pECXv/0JqfPtfKJ9/I7bOODF1x/WBJUmP/hoqyRuvST+/SuRr6NdC+jD9kddqU48rRzrTd7nLXfP+ZNsdtUmJOsran7dJgr4Hu7wXr+oZpz8df6WDmEbUOukTd+96s/osnyt/sp81xm2T97YB2ndzsvpZ+vvt5Hcw8oricePd4UNc3THG2ePf4L+X+NuJn9lPPfrdKkrvfdQnv5h6/8z7XNvDLvbfKcmYrzZHm/l0oyhqt2j61ZOTk3vPmfZbq9/Mrsrqs6j3sIY82WPnBHNX1DdOm6PVa+/sS9/vlxqOr1HvGeOWsO+keH3P7ZJLaBF2qk/FHlHAm915tX0buZ+uNB35XljNbhmHI5OOltSu+yu1rGQcV9cdubdj3m3BxMZlNVfbvYsakBQAAAAAAAAAAAAAAUCW8qjoAAAAAAAAAAAAAAAAuehf3ggdVhpUWAAAAAAAAAAAAAABAlWClBQAAAAAAAADA/7N35/FZVIf+xz8zz5p9IQsEMAlbWBIIi6xCBLSKWEq5ikURXFEUl9YN71VvUbx4rWgFsZZqq60Voa1VUKoVLVhBQATZFyGChCUEsi/POs/vjycZjaCXxf5S2u+7r7zKM8+ZM+ecOXPOmXmOZ0RERETkTBlaauF0aKUFERERERERERERERERERERaRGatCAiIiIiIiIiIiIiIiIiIiItQq+HEBEREREREREREREREREROVOmXg9xOrTSgoiIiIiIiIiIiIiIiIiIiLQIrbQgIiIiIiIiIiIiIiIiIiJyprTQwmnRSgsiIiIiIiIiIiIiIiIiIiLSIjRpQURERERERERERERERERERFqEXg8hIiIiIiIiIiIiIiIiIiJypgy9H+J0aKUFERERERERERERERERERERaRGnNGlh7ty55OXl2X8DBgxgwoQJrFix4rQOvn//fiZPnkzv3r3Jy8tj+/btpxVPSykvL2fmzJlcfvnl5Ofn07t375Ped8SIEc3KsunvhRde+Aem+NS89tpr5OXlUV5efkr7/eUvf2Hq1KkMGzaMwsJCfvCDH/DHP/6RSCTyD0qpiIiIiIiIiIiIiIiIiEgLM1vw7yx2yq+H8Hq9vPTSSwAcOXKE5557jptvvpnf//739OnT55Tievrpp9m/fz9z5swhISGBnJycU01OiyotLWXp0qX07NmT/Px8du7ceUr7X3TRRVx33XXNtmVlZX2XSWwRL774Im3btmX69OmkpKSwatUqHnzwQQ4fPsy0adNaOnkiIiIiIiIiIiIiIiIiIvJP4pQnLZimSWFhof25V69eFBUV8frrr5/ypIXi4mL69evH0KFDTzUZ/xTy8vJYtWoVEF2F4lQnLaSlpTUry38Vv/jFL0hNTbU/Dxo0iMrKSn7zm99wyy23YJpn+VQfEREREREREREREREREZGvM4yWTsFZ6Yx/Pc7MzCQ1NZWDBw82275hwwYmTZpEYWEhffv25a677uLYsWMAlJSUkJeXx9atW3njjTfIy8tjxIgR33iMQCDAzJkz6d+/P/369eOhhx5iyZIl5OXlUVJS0izck08+yfDhw8nPz2fUqFEsWbKkWVzTp0/n0ksvZc2aNYwdO5bCwkIuu+wytmzZ0ixcJBLhhRde4KKLLiI/P5+RI0fy4osvNgvzj/zx/VTysmrVKr7//e/Ts2dPJk6cSElJCZWVldxxxx306dOHCy64gKVLlzbbd/ny5Vx77bUMGjSIPn36cPnll/PBBx98J+n66oSFJt26daO2tpb6+vrTKA0REREREREREREREREREflXdMorLXxdXV0dVVVVtGvXzt62YcMGrr76aoqKinjqqadoaGjg5z//ObfccgsLFy4kIyODhQsXct9995Gdnc0tt9yC2+3+xmPMnj2bV199ldtvv51u3brxzjvvMHv27OPC3XHHHaxfv55bb72Vjh07smLFCu655x4SExMpKiqyw5WVlTFz5kymTJlCQkICs2fPZtq0abz77ru4XC4AHn30Uf7whz9w880306tXL9avX88TTzyBx+NhwoQJZ1psQHRiRCgUsj8bhoHD4TjlvDz22GNMnToVp9PJzJkzufvuu4mJiaFfv36MHz+eRYsWcc8999CrVy/atm0LRCeODB8+nOuuuw7TNPnggw+YMmUKL730EgMGDPjGNJ9sur7uk08+ITMzk/j4+DMtNhERERERERERERERERER+RdxWpMWmn5oP3LkCD/72c+Ii4tj0qRJ9vezZ88mPz+fZ555BqNxCYwuXbpw6aWXsmLFCoqKiigsLMTr9ZKamvqtr0iorKxkwYIFTJ06lSlTpgAwdOhQrrnmGg4dOmSHW716Ne+//z4vvPAC5513HgBDhgyhrKyMuXPnNvtBvaqqipdffpnOnTsDEBMTw6RJk9i4cSP9+vXjiy++4OWXX2bGjBlcccUVAAwePBifz8e8efO44oorvpNVFl555RVeeeUV+7PD4WDbtm1nlJcjR47wyCOPcOONN3LrrbcCUFBQwLvvvsuyZcuYPHkyABMnTrTjsCyLAQMGsHv3bhYtWvSNkxZOJV1ftW7dOpYuXcp99913ukUlIiIiIiIiIiIiIiIiIvJPzdDrIU7LKU9aqK+vp0ePHvZnh8PBs88+S4cOHQBoaGhg/fr13HvvvYTDYTtcTk4Obdq0YfPmzd/6X+R/3a5du/D7/YwcObLZ9pEjR/LRRx/Zn1euXElycjIDBw5stnrB4MGD+elPf0o4HLZXMcjIyLB/5Afo1KkTAKWlpQCsWrUKgO9973vHxfWrX/2KQ4cO2SsWnIlRo0Zx/fXX25+bKvGZ5CUnJ8cO2yQxMZHU1FQOHz5sbzt8+DBPPfUUq1atoqysjEgkAtDs3H7dqaTrq8f58Y9/zIABA5pNbBERERERERERERERERERETnlSQter5eXX36ZSCTC3r17mT17Nvfddx9LliwhIyOD6upqwuEws2bNYtasWcft/9XVEU5GWVkZACkpKc22t2rVqtnniooKKisrv/FH97KyMlq3bg1Ef8T/qqZXQvj9fjuuSCTCwIEDTxjXdzVpITU1lYKCguO2fxd5SUhIaLbd7Xbb+bMsi6lTp1JTU8Ptt99OdnY2MTExzJkz51vPz6mkC6C6upobb7yR5ORk5s6d+52sTiEiIiIiIiIiIiIiIiIi8k9JCy2cllOetGCapv1De8+ePcnNzWX8+PHMmzePGTNmkJCQgGEY3HTTTVxwwQXH7f/1yQf/l/T0dCD6g3lmZqa9/dixY83CJSUlkZqayvz5808YT2pq6kkfMykpCcMweOWVV+xJAF+Vm5t70nGdju8yLyeyb98+tm3bxrx585qdI5/P952ly+fzcdNNN1FTU8PChQuPm0QhIiIiIiIiIiIiIiIiIiJyypMWvq6goIDRo0fz2muvMW3aNNLT0yksLKS4uPiEqwicqs6dO+PxeFi2bBldu3a1ty9btqxZuMGDB/P888/jcrmahTsdgwYNAqCyspIRI0acUVyn47vMy4k0rbjw1QkZBw4cYMOGDfbrJc4kXaFQiDvvvJPi4mJ+//vfN5tsIiIiIiIiIiIiIiIiIiIi0uSMJy0A3HLLLSxdupSXXnqJu+++m3vvvZfJkydz5513Mnr0aBITEzl8+DCrVq1i3LhxDBgw4KTjTklJYcKECTz33HN4PB66devG22+/zd69ewHsVw4MGTKE4cOHc8MNN3DDDTeQl5dHQ0MDu3fvZt++fTz66KMnfczc3Fyuuuoq7r33Xq6//np69epFMBhk7969rFmzhmeffdYO+/bbbwOwe/duwuGw/bmgoOC0XyHxXeblRDp06EDr1q2ZPXs2lmVRX1/PnDlzyMjI+E7SNWPGDP72t78xffp0amtr+fTTT+04unfvjtvtPqP0i4iIiIiIiIiIiIiIiIj80zH1fojT8Z1MWujQoQOXXHIJCxYs4KabbqJPnz688sorzJ07l/vvv59gMEjr1q0ZOHAg2dnZpxz/XXfdRSgUYv78+ViWxYUXXsiUKVN4+OGHm712YM6cOcyfP58FCxZw4MABEhIS6Ny5M+PGjTvlYz7wwAPk5uaycOFC5s2bR1xcHLm5uVx88cXNwt1xxx0n/Dxr1qzTOu4/Ii9f53a7mTt3Lg8//DB33HEHbdq0YerUqaxevZotW7accbpWrlwJwGOPPXbc/u+99x7t2rU74zyIiIiIiIiIiIiIiIiIiMjZ75QmLdx2223cdtttJ/zuiSeeaPa5oKCA+fPnf2t8b7zxxkkd1+128+CDD/Lggw/a2+655x7atm3bbNKC2+1m2rRpTJs27RvjOtEP6YmJiezcubPZNsMwmDhxIhMnTvzWtH19v5P1/vvvf+v3p5uXAQMGnDBNXz9ez549+eMf/9hs29ixY5t9Hjdu3HGTJE4mXf9X3kRERERERERERERERERE/uUYWmnhdHwnKy38o61du5b169fTo0cPLMti+fLlLFmyhOnTp7d00kREREREREREREREREREROQ0nRWTFmJjY1m+fDm/+tWv8Pv9tG3blunTp3PNNde0dNJERERERERERERERERERETkNJ0Vkxby8/N59dVXWzoZIiIiIiIiIiIiIiIiIiIiJ6a3Q5wWs6UTICIiIiIiIiIiIiIiIiIiIv+ezoqVFkRERERERERERERERERERP6pmVpq4XRopQURERERERERERERERERERFpEVppQURERERERERERERERERE5ExpoYXTopUWREREREREREREREREREREpEVo0oKIiIiIiIiIiIiIiIiIiIi0CL0eQkRERERERERERERERERE5EwZej/E6dBKCyIiIiIiIiIiIiIiIiIiItIitNKCiIiIiIiIiIiIiIiIiIjIGTJMrbRwOrTSgoiIiIiIiIiIiIiIiIiIiLQITVoQERERERERERERERERERGRFqFJC3JW8bod5Cd0w/A6qbcaMFPiiL+sO4bbSXmwgvo/fUp5oIJkVxKOgW2pC9UBcGh/FQD1viAdJlwE/jAJznj6JfUGINYRQztvFqWBIzSEG8iNyQZgUN9RVNUFiDG97Krbg9vjpZ03iydrn6N/1kDW7F5Blqc1K554lvJ9ezlY/gUAi0KL6d9+MCW+g+AwaNM9g3beLACq6ssBOFx7mAgR/JUNAPxm0K0ApLlT8ZhuUuI9dr4/ePklEj3JWA0BnB3SKJp9H+dm9qch3MCK/5wNQHH9XsaveZgEZzzZMefgTUjAObgdh/2lmF1b0S+pNy6nifOcNLxuB+297ciL64y3TTyG10W8M5bxzjHRA7oc1C1Yx+qtyzhwrB7v0C4ABBbv4ND+KjYtfweM6PI2qzf+lRLfQTymm5XL/wxuk8ixenJis0l2JZHkTMRjuikPVvCXyxbgdJhQF6ToP2/D76vHaBVDzLBskp1J1IcbGDJ8HMmuJGpCtQBUBqvoFNuB83tmkXJRby5aMBNnjAtvZis6XHkxAKX+IxhOB2+Nnc6Qkf8BwODB3yfg99ExtgMAQ8ddidNwcaiiAafHQ124js8b9uEx3QB0adWVwp9MIsvbmtyYbD4/upvsmPZkejJIaJXOQd8hAA74DlAeqMCKwJUjO7HfV0L4QDlxjjjqwnUsCi3GY7ppFZNGTFYGRbPvA2BA5/Nxu7wAOPu2pp03CxOTqrd348xMoq6mivyE7lg1fm79r+G4TCdVoWoAOqZ1IT+hO91z+7F6x/s4MpIAaOVqxcCuI3AYDuIccRC0WBRaTO26A+TGZNPOm0WqK4WBBRcCkOpKoSZUi5kZR6n/CIQtAKwaP5837APgvB/8iHVVGwDYXV9Mdkx7Ujrl0ubWUcQ6Yljzv78iGAlivb+PgBUgMT4F5zmtcGekEK6sY1PNVhaFFmNFLAhZ9EosoJ03i5ROubgMF6bXRbIziS012wit+ILQkSoMj5NeiQWU+o9QHqxgUWhx9BrKGoiJSWtPJkOGj8MsyCAtuTUu08nRQDnBSJBkVxLho9VkedvQzptFevtcDK+L4JoSrDo/SSlp9nUU44m+Ecn/yefR82C42Newn3R3Ggnj+5HujoZ1mU4Mt5ND+yv5fNdGEu+9gKAVpH//6PXUO7En6Z40NtVsxWE4MFwOANp521KQmo/LdBKMBMm75EIawtHru3LnHgAcGUk4DAexjhgyPRlsq93xZT2P70j5vr0YDhO/FQAg2ZnEqlVLou3fkE6N7VUsZCVghcK4zGgeBnbLJBwJc8Xyp3E4nJhel30+TcMkGAnibJdKJBiGSIQurbriPKcV3eO7ktO+GxuqN9E+rj0Ax+qP0jU+D1/YT5IzkaS46DVyzpBzcF7amcpgFdtqd9A5pxf14QYGf388bVPOscs51ZXCM1NepyxwNFqvOqYwqPAiasPR9jjZlcyB9RvYXV+MIy0RgE+qPuULXwnDrrmW1p5MyvftpTJUxVd1iM3BXRCt01Whakr9R+iQ1YMt+ypo7cnETI/joP8QN637Bc7OrQhHwuypLwbAkxJD5fubqAhG47QiEQLlDYQjYfxWgM7dzyXL28ZOf5wzlg/f+QPtve1wGA4O1x4GwDRM0lLb4DQcELY47C+lXU5XasP1HPaX0i2+CzhM2FdFnDOOc9P6RetUn2jdGJrfhmRXEgfrD1IerAAgzhFHIOTH64i2+Q7DQXmwwq67neI7YnhdpMdkUB2oIhQJU+I7SKn/CLGOGMKRMHXhOla+9ycA4h1xVAdrSMjIsMsuNyYb/GG6xXfhvIsvB6Lt5pALL8NluMDp5NzM/hTX78VhOFm4ohgzJY59DftZFFoMQPqkYdSHG+iVWECaO5WIZeFolQCAu7EdPeg7zH5fCQ7DQTgS5kSCWw5TG66jU0In0t1p9jVybmZ/BnQqYkRhFm+NnU7/7CEcDZQTjoTpnz2E7rn9aLB8APQb/n1c8W4+XPIqf7lsAZWhKmJ/1Acz3kvIHz2uo20CSc5EttXuIMYRQ5anNZH6AA7TIIJF28b2Ijc2205bU5sbiUBrTya3PjWa+nAD7WLbEi6poSpUjcNw0CYzm001W+nfvx3ewZ2xQtFjtve2w8Qk2BAg4g8RtILUhxuIdcSws+4zglaQWEcMWd421IRqKXzzdlJ6d6PUf4QEZzwjfvUQztGdIBLhRz/ojqN1sp22mlAtVaFqDhyrp723HcmuJMzMOOrqomnu0m8IAAd80boajAS/PP+degIw9EdX0yGtC76wH2t39LqpCdVSdE90/LHiP2cz3jmGK0d2omHZDlyGi8zBvcEw7D7JM6QT9Y3nLNYRQ5o7lc8b9tE3qRCIlpuFZR/bmZWKiYGrT1syPekYXhemw4yODQy3Pd461nCUGEcMQ390NVUNFXhMN6u3vQdA+EgV7p7tOewvpY0nk+DmUhKc8XSafz1H7nsHvxXA0y6dhLRMAJKc0XalPFjBQd8h1pZ8hMNw4DJcpLpSGDz0B3hNj53ORaHFxDpiOO/SK9i84yN7XJAbEx3HHA2U29drqiuFssBR/FaAmlAtAwsuxEyPpVdiQbM6nx3Tnt31xXQ7J4Vu8V3ontuPtXv/Tl24jhWz5lIfbmBRaDEjf/NTOsTmkNS7i90HdYrtQG5SRwDadkilU2ZXeuX0p0NaF877/o/wml5wmMTHuOgQm0N5sIIO8blkutMpCxylrrGt3e8roXdiTxznJHF06w56JvSgMlhFe287FoUW402N5eoP53Kwsc7srPsMX+M15jHdJLuiY41IMIzP8mFisq9hP4bLwQe/fZG87Og5T3Onkh3TntXb3mNX3R5yhw6hT7+RVIaqcBgOusR1xGW47HFwkyRnIkmuRHyWj9yYbNLdaZgxbhzZSfRL6k26O43PG/bhMBwM7HEBAAWp+WTHtCfBGY/X9LKhepPdRrn75VAfbiC+fRvGO8fgPCeN/b4SPnznD5QHK2jvbUdGfjcAzEFt2VW3h7yRIzjoO4zbdOMxo21wt6Su0Trd70Iy3Bl0iu2Az/KR6kphb/0+TEzS3Wl0iM2xz3myKwmj8bbaYTho5W5Fp8bxZ5IzmseddZ+R2CO6zWW4GNCpiP2+Evq2G4CFRX5CdwZ0KiLOEUeyM5lz0/phYvJFwwEMw6Ah7CNgBVgUWkyiM5H09rkcDZRTH26wx9nBz48QjARxm242VHyKe3A2qe7kaN8EBN8tptRfRro7jXR3GuFImARHtK3sEJtD24eK6H7uMByGA78VYGP1ZsoCR9ldV0yXzn0o9R8hP6E7ya4kRl7Rk3Mz+0N2EhPO78ii0GISnPF2X7qrbg8ldSXROuJqxeAhY6gL19nXUvf4rqS704h3xuIx3VQFq2l/c7TPDFgB0t1pxDhiWLtvJQmOBBaFFhOMBMn0pFPqP0K6O400dyrhSBiH4eDQ/kriHHGs+Ww5sY4YcmOyOeg7xJO1z+EwHCS7kunQrTee+DjMxnMVjoQJRaL3hDhMrEiksY9rRae4DnYfm+JKIalfV2IdMcQ5oul15WXR47yRJDuT8Teel9ae6FjM64iO9zvF5TLeOYZ2sW2pCdWQ4Eigd2JPdtcX037iBQSsAC7Txd82HiTZlUTPhB6097Zj9dZltPe2I8WVxLqK9SS7ktjXsJ9u8V1YvXUZESwchgMrErHzYXjcdv8OkO5Oo95qwP/J53zesI9bnxpNjw6pdI/vSlJaBnGOOOrDDaS6Ukh3p5HhziBcWsngoT9gUWgxqa4UAA77S7GwiG+XSLeeg+1rHqBLXCeyPK1p48kkgkV94z1003XRL6UPHWNzSHImRMfrh6PtT5OttTv4rG437q6tyYzJ4IHPfsPdW56nMljFoD4Xk94+l1beVqS4kvGYbjzt0nEkx9EhNgeAjDbZmMlxeB0eusV3IaV9e+rDDfg37rP7c8PrJsWVZO8D0N7bltaeTJKdSVy0YCY14Rq8Di/JriTS3KlYWFjHaoDouKC1JxO/FaAqVI3X9GAaBqu3vYcZ48ZpOHAaDsr8R+nYdwBt4rNo722H1/TafVFeXGfCkTDp7jRK/UfIjcnmb3/YguFyUBWqbnbue2QW0ComjWAkRFngKA7DYad7XfknANSuPcCwG65jd32x3W9YkQgDOp9PO28W3eO70tabRZe4jvRO7ImFRYfYHNrER9vgunAdRkw0H20ys9nXsJ+c2Gx21xdDVgJVoWoMj5Oc60fRv90g9vtK6J8zFJ/lY3d9Mf1zhtpt3ZrdKwh9WhpNV7iOD99cSIormY5PXUumJyN6P5c9hExPBrkx2SQ44zExaePJtPsE0zDwWwFG/uanYEXs/AYjQdLdaazeugyP6bbb/cP+UnCYtGqsh76wn0xPBpW1fkzDIKV9ezt9AG0ys+mfM9Sue+WBCgbkDSdhQFdWrX2LrzKSo/2AgUFVqJqGsI/8hO5EsGjvbYeFxa66PRTdfxsOI3r+2nmz7OcAHtPNYX+p/fzDY7qxIhEmX9odw+1iYNcR0bL63SYchoOA5SfRmUi/pN4YhsHfX/kt451jKA9URPv6xnJtX1BIrCMGgFYFeQAcDZRHnzURHSNWNt7jRBrHNk3jwKY296DvEO28WVQEq6L9UiDM2r1/Z1fdHvuaBugR39U+9od/WWT301me1vb2WDPGLt+1+1ZyuPYw7bxZ1IRq2VUXvedtCjt4dLRdCkfC5MV1xmO6aefNIs3dirjMdMY7x1AWOApAfbiBlKR0INqHeB1eKoNVjWPoEAAxmWnRvj4tHZ/lw//J5yS5EmnVqysAZYGjHA2UE7ACZHnbsHrbewSsAJXBKrwOD72HjcJn+egc15F1VRui18j7+6L3Q4DlC+IwHMQ4YsAwyGvXyx5nQPQ+1mt6Ge8cQ+RYA/2zBtrf9UosIM4Zi8twcTQQfebnPD+bo4Fy/FbAPjcAjoFtAeyxQqS8gaOBcjrFdmBfw/5m9TLVnUKp/4g9Pu3ev4h23iz6JhXitwL0SiwgNybbHqsB1IbqcRgOttbuoLh+rz0Oqg83kB3THtMwMFO8dI+P9m0Fqfmkdu5gH3NQn4vt9iXOEcfRQDmZsZnsOlDF0UA5ZnosuTHZ5A4+hyOVB4lNSCTZlWTXU5fhIiOxDQM6DCMcCVMZrCI9rS1+K0BDuIGVH7zO0UA5pf4j5MV1Zr+vhF6JBbQd1p+BBReSmRKDVdtAv9S+5MV1tp+NVIWqadejAIfhoD7cQJIzkWE3Xh+t81YIr+llS802ho67knR3Grkx2QStEB++8Sq5Q6P3Sk35au3JpNR/hKPBY+RcO4pO86+nQ1oX1lVtYNika0h1peC3AiS7krl53XOkuJJp721nj/d8lo+0+AzOGzsBiLZlae5UDKdJnCPOvs8o8R20+6SEjAw+b9hHqf8I7bxZHPQdIi0+g8Rz2jKo7yjO+8GP6BCbw7zb3wSwn8vd8c5kdtcX89Gn73D4vr9Gx+MeN4OH/iAarzMeKxLBbwXom1SIKyf6HGBg1xF8+OZCMj0ZdIvvgndwZ/4w/E4y3RnR58HxnRnYLZMPXn6JJGciRpKbJGciRwPHojfEjSaNjo6fOzfev6e5U/F8vytd4jqS17qHXTddhotubXvRL7UvgH3tVAarouO4xus4GAmSmRJDiiuJ2IREEpzx5MZkc6xxXBsdt0XvwQadewkr/mcuDsNBqf8IkUAo2tdbAfr1u5BFocV06X4u4UiY4vq9WDUBdtXt4cM3F9r3rGnuVLYd2QJA0X/exoAOw0hyJvLRp+8QY3qjz0bTYglGgoQ/+MI+d+nuNMY7xzCw1/eIc8ThtwLRe9VgNfXhBurDDXRP64EZ68Z6f5+9T6uEDIpuv5k0dyoOw0HC+H6Ul5fSNq87HWNzeGHRRoKRIB7THR2f+KLlEolE6BIXfeZXNH1atK1obGvrww2smDXXvg76JfVmXdUGPL2yOewvpSA1nx+teJona5+j3mrAVxugPFhB3+5FWJEIQStEe287+3ltgjOe+nCDXTcBhl45id31xVy6+HGKHrsbiD4TLvsgWg8P+0tp5WrFJee2/2oTxbbaHaS706LPibHo336wPRbM9GTgNb32OGdRaDFVoWrGO8ewrmoD5cEKusR15JOqTzFTvHxx3e+oClUzoMMwHOmJFGT2oipUTawjhpG/+Smxjhj7vFYGqzjiL6NLXPS+uandzYnNpi5ch1Vex3jnGDuPnx/dbbe5sY4YGsJ+2uXl23UyJy6HAR2GAdF2b3d9Mau3vcd45xiGjrsSgD+OuJMEZzzh0lo7/+OdY7j6w7lEiDCoz8X0bzfIvqfOjcmm7oG3cfdvZ99bQ/ReZ0vNNtontKdVTJr9mxRg/7+FRSQQYlDfUQB0i+9C+4JCzk0/FznLGC34dxbTpAURERERERERERERERERERFpEc6WToCIiIiIiIiIiIiIiIiIiMhZzzjLlzxoIVppQURERERERERERERERERERFqEVloQERERERERERERERERERE5U6ZWWjgdWmlBREREREREREREREREREREWoQmLYiIiIiIiIiIiIiIiIiIiEiL0OshREREREREREREREREREREzpTeDnFatNKCiIiIiIiIiIiIiIiIiIiItAittCAiIiIiIiIiIiIiIiIiInKmDC21cDq00oKIiIiIiIiIiIiIiIiIiIi0CE1aEBERERERERERERERERERkRah10OIiIiIiIiIiIiIiIiIiIicKS0ZcFpUbCIiIiIiIiIiIiIiIiIiItIiTmnSwty5c8nLy7P/BgwYwIQJE1ixYsVpHXz//v1MnjyZ3r17k5eXx/bt208rnpZSXl7OzJkzufzyy8nPz6d3794nve+IESOalWXT3wsvvPAPTPGpee2118jLy6O8vPyU9luxYgUTJ05k4MCB5OfnM3LkSGbNmkVNTc0/KKUiIiIiIiIiIiIiIiIiIi3MMFru7yx2yq+H8Hq9vPTSSwAcOXKE5557jptvvpnf//739OnT55Tievrpp9m/fz9z5swhISGBnJycU01OiyotLWXp0qX07NmT/Px8du7ceUr7X3TRRVx33XXNtmVlZX2XSWwRlZWV9OzZk6uvvprk5GQ+++wz5s6dy2effcavf/3rlk6eiIiIiIiIiIiIiIiIiIj8kzjlSQumaVJYWGh/7tWrF0VFRbz++uunPGmhuLiYfv36MXTo0FNNxj+FvLw8Vq1aBURXoTjVSQtpaWnNyvJfxQ9+8INmnwcMGIDb7ebBBx+ktLSUzMzMFkqZiIiIiIiIiIiIiIiIiMg/hnGWr3jQUk7p9RAnkpmZSWpqKgcPHmy2fcOGDUyaNInCwkL69u3LXXfdxbFjxwAoKSkhLy+PrVu38sYbb5CXl8eIESO+8RiBQICZM2fSv39/+vXrx0MPPcSSJUvIy8ujpKSkWbgnn3yS4cOHk5+fz6hRo1iyZEmzuKZPn86ll17KmjVrGDt2LIWFhVx22WVs2bKlWbhIJMILL7zARRddZL/i4MUXX2wWxjTPuPi+Nc8nm5dVq1bx/e9/n549ezJx4kRKSkqorKzkjjvuoE+fPlxwwQUsXbq02b7Lly/n2muvZdCgQfTp04fLL7+cDz744DtJ14kkJycDEAwGT74QRERERERERERERERERETkX9opr7TwdXV1dVRVVdGuXTt724YNG7j66qspKiriqaeeoqGhgZ///OfccsstLFy4kIyMDBYuXMh9991HdnY2t9xyC263+xuPMXv2bF599VVuv/12unXrxjvvvMPs2bOPC3fHHXewfv16br31Vjp27MiKFSu45557SExMpKioyA5XVlbGzJkzmTJlCgkJCcyePZtp06bx7rvv4nK5AHj00Uf5wx/+wM0330yvXr1Yv349TzzxBB6PhwkTJpxpsQHRiRGhUMj+bBgGDofjlPPy2GOPMXXqVJxOJzNnzuTuu+8mJiaGfv36MX78eBYtWsQ999xDr169aNu2LRCdODJ8+HCuu+46TNPkgw8+YMqUKbz00ksMGDDgG9N8sukCCIfDhEIhdu/ezbx58xgxYkSzeiIiIiIiIiIiIiIiIiIiIv/eTmvSQtMP7UeOHOFnP/sZcXFxTJo0yf5+9uzZ5Ofn88wzz9hLYHTp0oVLL72UFStWUFRURGFhIV6vl9TU1G99RUJlZSULFixg6tSpTJkyBYChQ4dyzTXXcOjQITvc6tWref/993nhhRc477zzABgyZAhlZWXMnTu32Q/qVVVVvPzyy3Tu3BmAmJgYJk2axMaNG+nXrx9ffPEFL7/8MjNmzOCKK64AYPDgwfh8PubNm8cVV1zxnayy8Morr/DKK6/Ynx0OB9u2bTujvBw5coRHHnmEG2+8kVtvvRWAgoIC3n33XZYtW8bkyZMBmDhxoh2HZVkMGDCA3bt3s2jRom+ctHAq6QIYPnw4paWlQPScnWiiiYiIiIiIiIiIiIiIiIjIv4R/3EL9/9JOedJCfX09PXr0sD87HA6effZZOnToAEBDQwPr16/n3nvvJRwO2+FycnJo06YNmzdvPu7H7W+za9cu/H4/I0eObLZ95MiRfPTRR/bnlStXkpyczMCBA5utXjB48GB++tOfEg6H7VUMMjIy7B/5ATp16gRg/8C+atUqAL73ve8dF9evfvUrDh06ZK9YcCZGjRrF9ddfb39umuBxJnnJycmxwzZJTEwkNTWVw4cP29sOHz7MU089xapVqygrKyMSiQA0O7dfdyrpApg/fz4NDQ3s3r2bX/ziF9x888385je/aRZGRERERERERERERERERET+fZ3ypAWv18vLL79MJBJh7969zJ49m/vuu48lS5aQkZFBdXU14XCYWbNmMWvWrOP2/+rqCCejrKwMgJSUlGbbW7Vq1exzRUUFlZWV3/ije1lZGa1btwaiP+J/VdMrIfx+vx1XJBJh4MCBJ4zru5q0kJqaSkFBwXHbv4u8JCQkNNvudrvt/FmWxdSpU6mpqeH2228nOzubmJgY5syZ863n51TSBdC1a1cAevfuTUFBAT/4wQ949913ufjii7/xGCIiIiIiIiIiIiIiIiIiZ6XG/0hdTs0pT1owTdP+ob1nz57k5uYyfvx45s2bx4wZM0hISMAwDG666SYuuOCC4/b/+uSD/0t6ejoQ/cE8MzPT3n7s2LFm4ZKSkkhNTWX+/PknjCc1NfWkj5mUlIRhGLzyyiv2JICvys3NPem4Tsd3mZcT2bdvH9u2bWPevHnNzpHP5/uHpSsvLw+Xy8UXX3xxeokWEREREREREREREREREZF/Oac8aeHrCgoKGD16NK+99hrTpk0jPT2dwsJCiouLT7iKwKnq3LkzHo+HZcuW2f/lPsCyZcuahRs8eDDPP/88LperWbjTMWjQIAAqKysZMWLEGcV1Or7LvJxI04oLX52QceDAATZs2GC/XuK7TtfGjRsJBoO0a9futNIsIiIiIiIiIiIiIiIiIiL/es540gLALbfcwtKlS3nppZe4++67uffee5k8eTJ33nkno0ePJjExkcOHD7Nq1SrGjRvHgAEDTjrulJQUJkyYwHPPPYfH46Fbt268/fbb7N27F4iu/AAwZMgQhg8fzg033MANN9xAXl4eDQ0N7N69m3379vHoo4+e9DFzc3O56qqruPfee7n++uvp1asXwWCQvXv3smbNGp599lk77Ntvvw3A7t27CYfD9ueCgoLTfoXEd5mXE+nQoQOtW7dm9uzZWJZFfX09c+bMISMj4ztJ17Rp08jPzycvLw+v18uOHTt44YUXyMvLO+HqGyIiIiIiIiIiIiIiIiIiZz29HuK0fCeTFjp06MAll1zCggULuOmmm+jTpw+vvPIKc+fO5f777ycYDNK6dWsGDhxIdnb2Kcd/1113EQqFmD9/PpZlceGFFzJlyhQefvhhEhIS7HBz5sxh/vz5LFiwgAMHDpCQkEDnzp0ZN27cKR/zgQceIDc3l4ULFzJv3jzi4uLIzc3l4osvbhbujjvuOOHnWbNmndZx/xF5+Tq3283cuXN5+OGHueOOO2jTpg1Tp05l9erVbNmy5YzT1bNnT5YuXcr8+fOJRCK0bduWyy+/nOuvvx63233G6RcRERERERERERERERERkX8NpzRp4bbbbuO222474XdPPPFEs88FBQXMnz//W+N74403Tuq4brebBx98kAcffNDeds8999C2bdtmkxbcbjfTpk1j2rRp3xjXY489dty2xMREdu7c2WybYRhMnDiRiRMnfmvavr7fyXr//fe/9fvTzcuAAQNOmKavH69nz5788Y9/bLZt7NixzT6PGzfuuEkSJ5OuKVOmMGXKlG/8XkRERERERERERERERETkX47Z0gk4O30nKy38o61du5b169fTo0cPLMti+fLlLFmyhOnTp7d00kREREREREREREREREREROQ0nRWTFmJjY1m+fDm/+tWv8Pv9tG3blunTp3PNNde0dNJERERERERERERERERERETAMFo6BWels2LSQn5+Pq+++mpLJ0NERERERERERERERERERES+Q3qrhoiIiIiIiIiIiIiIiIiIiLSIs2KlBRERERERERERERERERERkX9qej3EadFKCyIiIiIiIiIiIiIiIiIiItIitNKCiIiIiIiIiIiIiIiIiIjImdKSAadFxSYiIiIiIiIiIiIiIiIiIiItQpMWREREREREREREREREREREpEVo0oKIiIiIiIiIiIiIiIiIiMiZMoyW+zsDe/bs4dprr6WwsJAhQ4bw+OOPEwgETmrf0tJS7rvvPgYOHEjPnj0ZNWoUixcvPqXjO08n0SIiIiIiIiIiIiIiIiIiInJ2q6qqYvLkyeTk5DB37lxKS0t57LHH8Pl8PPTQQ9+675EjR7jiiivIzc3lkUceIT4+ns8+++ykJzw00aQFERERERERERERERERERGRM3WGKx60hFdffZW6ujqeeeYZkpOTAQiHw8yYMYObbrqJzMzMb9z3Zz/7Ga1bt+b555/H4XAAMGjQoFNOg14PISIiIiIiIiIiIiIiIiIi8m/ogw8+YNCgQfaEBYBRo0ZhWRYrV678xv1qa2v5y1/+wpVXXmlPWDhdWmlBRERERERERERERERERETkTLXgkgEjR4781u/fe++9E24vLi7mP/7jP5ptS0xMJD09neLi4m+Mb+vWrQSDQZxOJxMnTmTDhg0kJyczduxY7rzzTlwu10mnXSstyFnl2fw72Va7g7V/WsRB3yE+eu/PXDu2Bx9vX85/7foNznPSMA0DE5MD//sGh/ylAFz7w3wA5hTexLRf/ZDNv/kT93/+LI5WCQBk/+Ea+r1xN34rwEH/IUp8B5l79R/Y9OkHPJ/7P3zhKyHdncb6o+vZU7+XJ3JmkfT4JYx+/THWVW1gUWgxXzQcoMR30E5rzF3DGHL+D/n4Zy/watEddlqchotrPFdw2F9KZbCSzdc9C8DUT54DoK23LV3j81jy5Id2XEPHXcnGik2s3vwuH735BwaNziNmTAFZnjac/9wDjHeOwTAM1v/X+3zRcIANVZvYcOgTPn50PnGOOLb97+8pD1ZwR8aPWLVyMVuvXEhNuIak9NZsvPYZPlr/NkcD5SwKLWbxJXezZtVbmDFuXvG/zmf/8Ts+Xvpn5j36N368ZqpdlivufhyAop/cQnZMewxMzs3sz7H31hN8fQcbqzcTsAJ07diXrvF5lPrLGPP6VdyVPpF1v/w9KefnsrV2B9vm/YHcjq3YU1/Mvob9hPYfY2P1FtLdaQC4TTfpXToz3jmGv//x9+R1S+fv1z7Kts/XET+6MwAOw8G28m0sCi1mw/KlANz5wY1srN7MzrrPAGh1cz/qwnV8NOpxPi77mBLfQfql9qW1J7qkzcela6l8bgUlvoP0fO02nqp+nqpQNQmOeD75YjWdYjsAcDRQTs/EHvxuyHOMd44h1hHD2oOr6ffz2+ke39VOz8aKTazZ+TcGjc4DwHt1b9aVfwLAmid/TVngKOmeNHxvbmPlB69z0H+IpP7dWLnsT4x3jiEnLoeXfa8DsP7wOsoCR1nz2XLu3vI8az5bTro7jd31xYx773pu+PgZerTpyUd/fQ2AWx++kDYF+ZT4DnLQf4i9uzYBkOpKoa03iw9e/A0dYnPYcGAdXTr3YeWyP9EvtW807edn0zepEIBz2wxgX8N+Ptn0N1Y8/gx+K0DPc86NVkqPg/JgBV9U7mXl8j+zZvcKttfupLUnkweT7iL7nG6seOBJYrJbs6tuD59s+huxjhjWHVzLnvpi2nmziPt+F7ZUbmX9rg/Z1/AFWd429E7sCcCDSXcR+9AFDL70chrCDexe9SEr/ms2Hx9aQ324ge7xXUlwxpPmasXWo5txGU721O9l256P+eiTv5DzxEUU1xSztuQj+zr6ebdpAOyp2gPAEX8ZHtNNp4Jz2fm7N6kPN/BZ3R4qg1V8vH05DdvKiDVj8L+ykW7nj6SqNkBuTDYx+dl0ffx6Bg+8lHhnHLuO7QCgzbM/4pOj66kMVlH08I/ZsGQxWZ42ANSG6vl0z1HW7f471aFqSv1lbKnZRjtvFgDtvFmsq1gfvX5XvkOcIw6AnXWfkRuTDcDqPy0CoNR/hBXT/ocPLptJVbCaX1b+gecXbqTEd5BhBW1YX/Ep6w6uBSBUfIyDvkMAbPn7Mj4u+5iDDYdYf+QTVi7/M/t9Jewv2UX/nKFsqdwKwGF/KRurN0frp+XjucHRtmnx+f/FxeMLKPEdZHD/0az5bDmFv76dHe/8lc+O7uCK5U8D0CE+l2nzxzJ48Pfxml4+vPNx3N/vSnmwAoCDvkP8rGYe+Qnd+fizD6LtyI+nkh3TnsCGA+T/cipfNByg1H8EgHmP/i3aNo4dxt9fe4XP6vaQ7k6jLHCUrfvXMyy/NbGOGD58fQFBK0RZpQ8jNjoQ6hzXKdpeXfEwu+uKiXXE2OW94o5Z9EntTe/Enqz59F06XjoCgLzCQdSEahkybCwH/YcIR8Ic9peS6cmg8MXbWVvyESW+g6xa/SbhSJjVO97noO8QvXoVsb12F5vKPmXF/OfZUrONQMDP9uXvseG3i/jk6HoeyppCJBKhJlRDljdaNxKc8eys+4yGcAMASc5EjgWO2XV3fcWnfPTJX9hQ8SlHA+U0hBtId6fRKbYDrVytODezP93ju3LRK48AsKlmK8muJHbu30ivxAIAer52G+uefZl1VRso/3AzAH2TCgluP8DnDfswvS5ixhRgYVETquGKog4Ur1tDXnxn5t0dbVN73tiX/tlD2NfwBTnxufztP2awZvcKAHbXRwetAStArCOGmlCt3ed9XbismrLAUdaVf8L22l1UhaoBMGI8RPxBxjvHsCi0GMIW/bMGkt0mjy8O72bNZ8s53BjnhuVLWXbNT/nvPS8x5vWrKPMfZcXcX7Jt7QqWXxcth5rFGzAMg9yYbI4EjrChehOrd7zPXWmT8FsB9jXsZ9uej9lSsw2A8c4x9E7uBcCDGbfis3zMe/RvdIvvwrqK9Xy45FXS3Kl4TDdVR49wbmZ/qmoDfPiXRXxw2UwAIlhYWLw1djpr9/6dbuePJNWVwhNlL1E05QYAfGE/daE6HIaDNy+Yzicr/8K5bQbQ64JRhHcd4/LrzuVgwyFevPMtPt65wi633ok9yY3J5rP/+B0RLExMPnjxN+z3lQBwyYLx0Ws+EgQg05Nh77t66zLeXV+C2SGZTYc/pSCzFyv/uIC868aQ5EzE//YuAM5/7gEWhRYz3jmGQF09rdyprFz2J9a8/We21+6iW3wXVr2+ELPx9qFbfB4VwSpchouKYCUADeEG+3uAVWvfotRfxobfLmJd1QZWb36Xt8f8F7sb+/z0jHaYmBwNHsM0DAJr97Grbg8Dp99Et/guVAarWFexnt1/+4AXfX+guH4vn6z8C1WhampmraD9nNF0iu3A6m3vsWX/OgBqw3XRMkvuRX5Cd4qm3EC8M450Txr7fSUEtpawrmoD3eK72GOAssBRtrzzNn2v+xFGY/rbFOTjNBzkxmQT74ijMlhFie8gvfuOoENsDg7DgVXjY/0tT/PDT+/Ga3oBeLZ8Ee3PH0Sn2A7cmfEjkjrmsOaz5QzuP5pkVxLDrrnWHuPcdHUffrThIT76YDH1jW1AanIGH5d9DMBvBt3K9sObWVP8AWsPrmbD0iW08WSyqexTpiRdRtaIASQ5E1lXsZ6ddZ8x6g//Q5e4jgy77jpiHbHsrPuMtQsXsqd+L5tqtjKo8CK7zhRP/jWDu2eSHdMegKLbb7bbjKpQNYXP3A7Ah68voH/7wSS6EuiX2pdNBzcwoPP5bP482s/UhupJciZSdP9t5MV1ZvWyPzee9yP0adWbfQ37cRgOttfuatYWuEwnB32HSHDGU+I7SH24ga2lmzH6tKYmVEuaO5VBfS4m1hGDq3trAD45up5ddXsYseSnRLDonzPUjm/9ktfpnz2Ej7cvZ1FoMatWLibWEcPYvz5Jv+uuZGP1FnZsWAXAittmsSi0mA//sgjDMKgJ1ZLsTKImVEtpfSkLAm+weu1fiE9MpiZcS12onjR3KlWhaiwsgpEge+qL7XNmYhKwou9o3FC9iYO+Q3zesA+AQ/5S8hO6k+nJYM2avwCwr2E/N66/jTR3Kmv3ryLdnUZscjI3rr+NUCTI7vpiDtUeJMYRg8t04jW97GvYj7/xGIf9pWzb8zGD+o5iYNcRBK0QTsPBjZ/fz9FAOZXBqmgb8asXqAhWsbN2d7TM+7TBZ/moDzdw0HeY7vFd2e8rwevwsr12F4uG38GBDZ9Gz+fDPybJmUj/nKF4TDebd66mQ2wOcelpBKwAS8f8js8rdrPix//L3Kv/AECJ7yDHAscA6B7flbrGa3F3fTGhAxX0zxpo9337fSV0HXMR22t34TW9+CwfFaW1AHhi46gPN1AdrOHczP52WXpMN8X1e8nytqE6WM2gP01n2I3X47N8NGwroyxwlKIpN+A1vSQ440l2Jdn142jgGB99+g6bDn9KfkI3AEb++r+pDFZxLFDO5sd+SztvFpurt7KtZgfba3fitwLEOGI4Fijn848+ss9DVaiaPR9+yMHVn7DfV2KP5TZXb6VPam82Vkf72e21u1gUWsy6ivUM/u19fN6wj8S7RtIptgPVr66lPtxAVbCaV4bdzqAF09lau4MIFkU338DOus84GiiP9jWhamIdMWT8eBSLQovZVbeHcCRMOBJmvHMMI3/932zZvw7/hmg5nZt+Ll3HXERdqI49VXvI9GQw79G/kZ4cQ1xMAmv3raTXucO5aMFMKoNVAGyr3cHHR9dhtooFIKNzl2h75Erh3Mz+vDV2Oh998he7TgPR+83qTdSHG8iJycbEJBQJ0yuxgDR3KobbyaaarRwNlFNcv5f1n3/EQf8he1yXn9Cdnqk9Kf9wM+sq1tMztxWZqTG082bhvqQL2/Z8zLqK9eyo/YyB067jk+0fsKb4A3yWH4A1xR/w6WcryW/fj3uPzGT1jvc5766bWFf+CT94ezYAn+3fjN8KkOpK+bKtqNpIvCOO4vq9+IorCFgBNlZvxsS0690nR9cD0b407z+v5Nw2A0hwxlNcv5eKYBWTVz3DF5s20NqTydFAOVne1qxatYSPj67DZTqpCdVSePtErlj+NPt9JUz59Cly0zrRO7EnbXr3pPWAdmxa8Gf65wwly9OGimAVwUiQ7Ue2sLFiE+FIiF6JBSQ5E3kiZxYA/VL6RNuv/5nL5Y9dRP+sgbhMFwN7fS967/LZB1QEq6gMVbHfV8IhfymJkwaSG5PNfl8JHx9dZ5fBrgObsCIRqo4e4Z6dv+Szut0UzfsvVkz7H9p5s/j40BpWPDOfdSVroufS5aBXYgHnthlAt1eusOMZOuFqLls4Hq/pJTetE4tCi9lR+xmxaXH4G89T8aHtnJOaS4PlY0P1JqpC1Wyv3cU5hdH89Ln7mmg/MO33FNfvBWBj9WZSXEnRa/p/7+HT6s180XCA6lA1vXoV8eFbC+0xocNwYEUs3r/kRdp727F6x/tAdDw93jmGqqNH8A7tgMd087P2j2IaBq6umaxc9ie6xHVkvHOMnZ9h/zmMQX1HkepKoTxYQfrUkXxeHx2XuEynPf7OHdOVLE8b0t1plPgOkupKIcvbhjhHHP1S++IynfTpewFVoWoG3DzJrq/OTunRNHdP44aPn6EmVEuECD7Lz6CL/4OimT9hUWgx3eK72O1Xcf1ePvp4KfltCqP1d+2yaNmPn2iPJerCdQQjQYqm3siuuuh9btHDPybL24ZwJAxAsiuJJ2uj93Q5sdk81eNmip75T4ZePpFOnXrbZZB8WX8SnPEATF71DAd9h4hzxLG9dhc+y9esDWi6jg/7S/E33gMMvXwiAKZhMPHDuVR/sAWA7Jj2JKVlUBuuY0P1JrbV7GDf/h0sCi1m6ISrGe8cQ5o7lY8PrWHz59HnUnfvfZLnq//E7EOv2M/Z1u35kP5ZA9lZspFOsR3YU7WHg75DrFq1hKKpN9IvpQ+5MdkkOhMp9R9h8qpnKMg+l/bedjSEGyhbu5HcmGw2Vm/hhjXP4slKA4/D7s/X7v07LsNFBIu1+1exbm/z/5rwaOAYXoeHRaHFfPDrX3Ptlp/Y3+X+8VpqQrXEOWPtMeGKB56kX2pfklyJ9rkBOPC/bwBw36HHMTFZ8Z+z6Z81kN31xXSLj7a/TXXzWOAYcY449jXsB2DH2r/zZO1zWBGLgu6DccfE0PO123i++k8MuWwCgD3Wy0/oTv+CkfRM6MGRwBFyY89he+0uKoJV4HZQXL+X7bW7+OToetZuXGanL+GuIXQdNwqIjtdSXSlsrtzMA9lX0z97CH9f9DIlvoPs+dlKTEzWHVxL57Su5LcpZLxzDK09mXxcuharup6ie25l2NWTWbt/FX2TCkl1J1M0+z56JvQgO6Y9bedMIM2dSkx2a9LuGoSroA0zOk5mw4F1xF3Zl9bXDrefEeXGZLN788c4DUf02scivDM67khyJXLtxz+n6H/v4dhf19N1zEVknNOBnlm9eWj3i6xe9udoHGmdKJp6I3n/eSVe00vQCnHrnEupmbWCjYfXc8OaZ/nRzy9hyGv34zJcbKzeTNu0WHbXFXPzrlkErABeh4dOsR1Yf3Q9BQ8WNdaNcsqDFXyy4I+cE9OWAZ2i2/ul9GFgr+8BsHP/RhYE3qB3Yk921xeT7Epi/dH17N2zhfUb3sPMiGN3fTG3zrkUgBvWPGufk0F9R/Hrmj8RPlTB0HFXsmX/OgJbo+e5MlhFO28W540az6663WzYvByASatuZlFoMaX+I2yr3cGHf1nEotBijgSO4jHdbKvZwXjnGIaOuxKvw4vZL4unKn5DXlxnDjYcYuKHc5vV//UVn1IXrmPQn6ZT/OSfSYpvxcaDn9Cn7wUAtPZksnbfSuKu7Gs/g3IZLrtNaR/TFoD+7Qczo+NkdtXt4Ytjn+ML++n52m2kJWZSF67jvBnRe5Ch4ydyeMtWFoUW4zJcZHoy+HT1u6S6Ukh1pbB23TsAfLzpPRJdCZw3+grWvbeYoofuYFFoMcMmTuaJnFk8UvpLe0yacn4uA167ipzYbAb1HcXnDfsY2OMCNv/v77jkT7NoeHc7DiP6XwcHI0EWhRZjVdbR69zhtPNmYXZIxmf5SHYl0T9rIJ+UrmPTwQ3gie6T5Exk/ZFP+OED5xOKhLlrxy/Y+bs32e8rYfXGv7Knfi/Xj4/eo577vR+wt2EfR2ZE24PW3kw2VEWf3YY3RNvZprakW3wX7tw4H4jed+S/fQODzr2EKW9O5Pe+1/nk6Ho2XPJMY108xntj/5tFocWs3hq9rvsXjKQscJTBA6N164uGA3SK7cBTFb+xz+/mP7zB99/8GTVbSvH/7lP7/D1SFR1TFXYeYrctX5Ubk43LdPFU6QIe+Ow3xPywJ7Nrov3Nnbuf5PYt8/jCV0IEyw6/KLSYQedeEi3fSISnj7wKbgc/rXyc8mAFznNasX3zR6w/vI6iB26nV+H5lEz7PX0u+YF93FF/nMVDxb8hrU8+rwbeoGdCDwB+cvhhusR15IblN3DV3+fSJa4jAE9VP88122cAkOxKpiBvID/5JPqMOM2dyvbqnTjPaQWA03BgYvJCzZ9YFFpMq5v7AbAotJiCQSO5/U9X2ulYFFrM0cO1ZHlaEz5cybqSNXzv99FnUufcOIpriu9nxS9+Ra+fTbX3KQ9W0L/dINYf28DGik30yOhpP4PIKRrCtR/No29SIR8fXcemT6PPTDNuHMlHHy9lW/m2486ByHeturqaxMTE47YnJSVRVVX1jfsdPXoUgAceeID8/HxeeOEFJk+ezEsvvcScOXNOKQ1aaUFEREREREREREREREREROQs9k0rKfyjWFZ0ctLgwYOZPn06AAMHDqSuro5f//rX3HrrrXi93pOKSystiIiIiIiIiIiIiIiIiIiInCnDaLm/05SYmEhNTc1x26uqqkhKSjrBHl/uB9GJCl81aNAgAoEA+/btO+k0aNKCiIiIiIiIiIiIiIiIiIjIv6EOHTpQXFzcbFtNTQ1lZWV06NDhG/fr1KnTt8br9/tPOg2atCAiIiIiIiIiIiIiIiIiInKmzsKVFoYNG8aqVauorq62t7399tuYpsmQIUO+cb+2bdvSpUsXVq1a1Wz7qlWr8Hq9/+ekhq/SpAUREREREREREREREREREZF/Qz/60Y+Ii4vj1ltv5cMPP+RPf/oTjz/+OD/60Y/IzMy0w02ePJkLL7yw2b4//vGPef/993n00UdZuXIlzz33HL/+9a+55ppriI2NPek0OL+z3IiIiIiIiIiIiIiIiIiIiMhZIykpiZdeeolHHnmEW2+9lbi4OC677DJ+/OMfNwtnWRbhcLjZthEjRvDkk0/y7LPPsmDBAjIyMrjtttuYMmXKKaVBkxZERERERERERERERERERETO1Fn6noOOHTvy4osvfmuY3/3udyfcfskll3DJJZec0fHP0mITERERERERERERERERERGRs51WWhARERERERERERERERERETlThtHSKTgraaUFERERERERERERERERERERaRFaaUFERERERERERERERERERORMaaGF06KVFkRERERERERERERERERERKRFaNKCiIiIiIiIiIiIiIiIiIiItIgWm7Qwd+5c8vLy7L8BAwYwYcIEVqxYcVrx7d+/n8mTJ9O7d2/y8vLYvn37d5zif6zy8nJmzpzJ5ZdfTn5+Pr179z7pfUeMGEFeXh5PPPHEcd/t3bvXLuM1a9acUprmzp17SulosnnzZu6//35GjRpF165duemmm045DhERERERERERERERERGRs4pptNzfWaxFV1rwer0sXLiQhQsX8sgjj+D3+7n55ptZv379Kcf19NNPs3//fubMmcPChQvJycn57hP8D1RaWsrSpUtp1aoV+fn5p7x/bGwsS5cuPW77m2++SWxs7HeRxJO2fv161q1bR/fu3cnKyvr/emwRERERERERERERERERETl7OFvy4KZpUlhYaH/u1asXRUVFvP766/Tp0+eU4iouLqZfv34MHTr0O07l/x95eXmsWrUKiK5wsHPnzlPa//zzz+evf/0rGzZsaLY6wltvvcUFF1zA4sWLv9P0fpurr76ayZMn2/8WEREREREREREREREREfmXZ5zdKx60lBZdaeHrMjMzSU1N5eDBg822b9iwgUmTJlFYWEjfvn256667OHbsGAAlJSXk5eWxdetW3njjDfLy8hgxYsQ3HiMQCDBz5kz69+9Pv379eOihh1iyZAl5eXmUlJQ0C/fkk08yfPhw8vPzGTVqFEuWLGkW1/Tp07n00ktZs2YNY8eOpbCwkMsuu4wtW7Y0CxeJRHjhhRe46KKLyM/PZ+TIkbz44ovNwpjmmZ2KlJQUBg0axFtvvWVv27ZtG3v37mX06NHHhX/99deZMGEC/fv359xzz+Xqq69m06ZN/+dxqqur+elPf8p5551Hfn4+48aN48MPP/xO8yIiIiIiIiIiIiIiIiIiIv8e/ql+Xa6rq6Oqqop27drZ2zZs2MDVV19NQkICTz31FI888gibN2/mlltuASAjI8N+HURRURELFy7kmWee+cZjzJ49m1dffZUbbriBp556CsuymD179nHh7rjjDhYuXMi1117LL3/5S4YOHco999zDihUrmoUrKytj5syZXH/99fz85z/H7/czbdo0gsGgHebRRx9lzpw5jB07lvnz5/PDH/6QJ554ggULFpxpkTVz6aWX8vbbb2NZFhB9NUS/fv3IzMw8LmxJSQljx47l6aef5oknnqBNmzZcddVVfP75598YfyAQ4Nprr2X58uXceeed/OIXv6Bjx47cdNNNp7wyhIiIiIiIiIiIiIiIiIiISIu+HgIgFAoBcOTIEX72s58RFxfHpEmT7O9nz55Nfn4+zzzzDEbjchpdunTh0ksvZcWKFRQVFVFYWIjX6yU1NbXZ6ya+rrKykgULFjB16lSmTJkCwNChQ7nmmms4dOiQHW716tW8//77vPDCC5x33nkADBkyhLKyMubOnUtRUZEdtqqqipdffpnOnTsDEBMTw6RJk9i4cSP9+vXjiy++4OWXX2bGjBlcccUVAAwePBifz8e8efO44oorvrOVCS644AIeeugh1qxZw8CBA1m6dClTp049Ydhp06bZ/7YsiyFDhrBp0yb+/Oc/85Of/OSE+yxZsoQdO3bwxhtv0KlTJyBafvv27ePZZ5/l6aef/k7yISIiIiIiIiIiIiIiIiJy1tHbIU5Li660UF9fT48ePejRowfDhw/nnXfe4fHHH6dDhw4ANDQ0sH79ei6++GLC4TChUIhQKEROTg5t2rRh8+bNp3S8Xbt24ff7GTlyZLPtX/+8cuVKkpOTGThwoH3MUCjE4MGD2b59O+Fw2A6bkZFhT1gA7B/zS0tLAVi1ahUA3/ve946Lq6ysrNlkiTMVHx/P+eefz5tvvsknn3zC0aNHueiii04Yds+ePdx6660MHjyYbt260aNHDz7//HP27t37jfGvXLmSLl26kJOTc1xeTvVciIiIiIiIiIiIiIiIiIiItOhKC16vl5dffplIJMLevXuZPXs29913H0uWLCEjI4Pq6mrC4TCzZs1i1qxZx+1/qj/4l5WVAZCSktJse6tWrZp9rqiooLKykh49enxjPK1btwYgMTGx2XculwsAv99vxxWJRBg4cOAJ4zp06BBt27Y9pXx8m9GjR/Pggw8CcN5555GcnHxcOdXW1nLdddeRmprK9OnTycrKwuPx8MADD9jpPpGKigq2bdt2wnJxOBzfWR5ERERERERERERERERERM46ppZaOB0tOmnBNE0KCgoA6NmzJ7m5uYwfP5558+YxY8YMEhISMAyDm266iQsuuOC4/b8++eD/kp6eDkR/fM/MzLS3Hzt2rFm4pKQkUlNTmT9//gnjSU1NPeljJiUlYRgGr7zyij2h4atyc3NPOq6Tcf755xMKhXjttdd4/PHHTxjm008/5fDhw/zyl7+ka9eu9vaamhp7MsaJJCUlkZeXx6OPPvqdpllERERERERERERERERERP49teikha8rKChg9OjRvPbaa0ybNo309HQKCwspLi62Jzecic6dO+PxeFi2bFmzH+uXLVvWLNzgwYN5/vnncblczcKdjkGDBgFQWVnJiBEjziiuk+HxeLj55pvZtGnTca+9aOLz+QCaTaJYv349Bw4caPaqi68bPHgwK1asICMjo9mkDxERERERERERERERERERkdPxTzVpAeCWW25h6dKlvPTSS9x9993ce++9TJ48mTvvvJPRo0eTmJjI4cOHWbVqFePGjWPAgAEnHXdKSgoTJkzgueeew+Px0K1bN95++2327t0LRFd+ABgyZAjDhw/nhhtu4IYbbiAvL4+GhgZ2797Nvn37TmmlgdzcXK666iruvfderr/+enr16kUwGGTv3r2sWbOGZ5991g779ttvA7B7927C4bD9uaCg4JReITFlypRv/b6wsJDY2FhmzJjBlClTKC0tZe7cuf/nRISxY8fy6quvMmnSJK677jpycnKoqalh27ZtBINB7rrrLgDKy8tZu3at/e+6ujo7L0VFRcTExJx0XkREREREREREREREREREzgqGXg9xOv7pJi106NCBSy65hAULFnDTTTfRp08fXnnlFebOncv9999PMBikdevWDBw4kOzs7FOO/6677iIUCjF//nwsy+LCCy9kypQpPPzwwyQkJNjh5syZw/z581mwYAEHDhwgISGBzp07M27cuFM+5gMPPEBubi4LFy5k3rx5xMXFkZuby8UXX9ws3B133HHCz7NmzTqt436TtLQ0nn76aR5//HFuueUWcnJymDFjBs8///y37ud2u/ntb3/L3Llzee655ygrKyM5OZnu3btz5ZVX2uE+++yzb8zLe++9R7t27b6zvIiIiIiIiIiIiIiIiIiIyNmrxSYt3Hbbbdx2220n/O6JJ55o9rmgoID58+d/a3xvvPHGSR3X7Xbz4IMP8uCDD9rb7rnnHtq2bdts0oLb7WbatGlMmzbtG+N67LHHjtuWmJjIzp07m20zDIOJEycyceLEb03b1/c7We+///63ft+tW7fj4h42bBjDhg1rtq2oqKjZ5xOdo/j4eO6//37uv//+bzzegAEDTjsvIiIiIiIiIiIiIiIiIiJnJS20cFr+6VZa+Edbu3Yt69evp0ePHliWxfLly1myZAnTp09v6aSJiIiIiIiIiIiIiIiIiIj8W/m3m7QQGxvL8uXL+dWvfoXf76dt27ZMnz6da665pqWTJiIiIiIiIiIiIiIiIiIiZytTSy2cjn+7SQv5+fm8+uqrLZ0MERERERERERERERERERGRf3tmSydARERERERERERERERERERE/j392620ICIiIiIiIiIiIiIiIiIi8p0z9HqI06GVFkRERERERERERERERERERKRFaKUFERERERERERERERERERGRM6WFFk6LVloQERERERERERERERERERGRFqFJCyIiIiIiIiIiIiIiIiIiItIi9HoIERERERERERERERERERGRM2Xq/RCnQystiIiIiIiIiIiIiIiIiIiISIvQSgsiIiIiIiIiIiIiIiIiIiJnytBKC6dDKy2IiIiIiIiIiIiIiIiIiIhIi9BKCyIiIiIiIiIiIiIiIiIiImdKSwacFhWbnFV8lg+/FcBvBXAZLiwsan1BIpEIW4rLWb3xrwCUBysoCxzFZ/kAGO8cA0C3+C72919V8fp2khM9RCIRglYIl+mky52DCEWCNIR9hCNhgpEg4UgYgLv33o9pGoTqg3YcpmHgMlwAPJn/c8Lv7SV0oIKgFWJgjwvscNtqd1AfbsBhOLAiEdJcqQD06ZTGeOcYGsL1BK0gK5541t7nnB8PIhgJEueIo1+XYfTplAaAYRh07pPFotBiIpEINK44Y2HhMp3UhxsIRYKUBY4StEJkejIwMVlT/EE0PNAurl00/ZjMe+hd+rcfTDgSJus345syhsNwsOK/n7LLMtOdgcd0AxB4fw9WJEIEi4b6WgxMjDgPJiZWJAJWhKAVxDQM3l9ejN8KEMGif9cMAIKRIL/oezMGJiYmhsdFrCPGzrvLdBGuqGXolZPol9Qb0zD43hszcRku3AkeACKNxwfwhf0AVNcH8Zpe+5xVvL0bgBLfwWi8hgvDNPBZfvtYMe0ycBkuMlrFYjSWict02nEAJDkTMRwOVu94n6LbbybZlUyyKwlqAgQjIZZvOogViRCMBDEx7XOFFcFhOOx6HOOIwW/5aSg7holJZbCKSEMAr+llUWhxdBcreo7CkTDhSAiAOn8Is7HpDkfCZKXG4jJNsCKYmDyZ/3PGO8cQrqrHxCQcCZPkTATAYTiIYEX/vzGNkbCF1/RimNHKE162l1Bjfs0Yj32OMj0ZhCNh1u79O3GOOP7+6u/wml6qgtV4TS9e00t9uAHTMElp355IMBy9Rivr7OvHYTiwsDAwSXDG407wEMEiGAniMlyYGFhE8/xI1Ww+//FLOAozo2mwgsQ6YhrDmXZ+HIaDZFcyXtMLQE2oFpfh4ovZqygPVthlDthhmq5/wzAwMCFs0aFbb2Icnui1Y7iIRCKE3t+Ly3TiPCcVw2lyqKIBCwusCIQsjAQv9eF6DMNgvHMMvr/sjn4P4AtRF67DaFwGKhgJUtgxDZfhItRYHiam3WY0MQ2D+nCD/TkcCRPTeD0EI0G77npMN76wH4fhwDAM/nrVgwQjQRZc85pdzgBH9nwGQJwjjqpQNQAHfYcIR8J4TS/JzmQy3ekQDtvtZVMZmxgErRChL44CUBWqZvfB6mZl6vQ4OW/JA1QGq4jxOBnvHEMwHGTB8j3g+LKeUhfEY3rs8xAKRwhHQl/GFROdQ7lj2xqCDdH2AqLtTVPb01RHg5EgpmHiMBx2GQesQDTtppNz89LBYeA1vZT4DgDgb/y+qe40lX8TC4vQ7mg+I3X+aO4TPMQ6Yuy667f8ONwOOw8mpp1+ExPD6bDPZ3ZMe7sdC0fC1IRqsbAIWAEMw2hWhqHG89p03VlYWJEv24umOhltB8L2/nHOuGZtpb8m0KwuVQar7H9ntIqlLlyH1/RS3VgPrIiF0XiNH9r3mZ2Ppjwc9pfidXopmNQbgC0fl2C4nLgMF9X+SgzMZnlskuxKttN6Iu4ebfGa3mZlB1BztBTCFhf+7uFofqpriUQiOFLjOOwvBbD3qQ830NqTyc6SSt5fXoxFtB1rCDfYxw1HwkQiESpClfb5b+q3vnpemtqF7/3+EQxnNP4UVxKRSMSuewADOp8PRK+PvQ37MFwODlU04DJcdr/T1H45DEdjnTC/bBPiXHa9DkXCmJj2mMaRFIeR6MH/1g4cpsFB3yE+eP7XX+7bmN6jwWNgRut2U/sW64gFIBiKhnU2nr+mPqPJ1jv/wiW3DIxe56HoGMH3zk78VoD4u4YA0LlPFgBFN99AwPJjGl9eL00sLLtd++q2fQ377bHWidSEau2y+ep4irBl1/GaUC2RYGO7kB5rxw3YdcDCss+ns2M6x4rLMQ0Dj+m260fTeTacDrymh0ggTH24nnAkjMNw4OqY2djCmXY6mvphvjKesPxBDEzcjXE3pSV8pIqAFYi2o8M6UhWqpnFIFU2XwwRndL+8uM4YjW2hERttt42MuGZtgGkaGIZBjCN6Pfpr6+zrYlDfUdSF6oFo3WsKA9DOm0XEF8JvBTAxqQ83YJjRfs3wRttUKxLBbwVwNtbJiC+Iu7F8dtZ9xpGqBrv9tMrqMBsHkiYmTs9X0pgaH82DI1pvne1S7b4qHAlH44xxUheus8sZIGJFSHDG2+OIrwp9pY2I9nUe6sJ1UFyJy3RRHqwkEgxjRSKE9pbb599jusnNSoweMxzmt29tB6LtguFyNjunya5kakqqMDLjsLDs/r9TbAcA2nvbRdsZw4HHdGNiUh6sIBKJYGERCYQwMI67Fk1MQl/JZ3mwolmYpnEWYPchBoadtggWYSt6flyGi0jjscIW9vk0GutAU1sR+Ur8ae5UakK1BItLsWob8Do8OAwn4a+MNZvGf5FIhBhHTLQ/nftLHIaDNHcqFhZ14To8pps4RyzJriSKnr6ffQ37o3k52hBtq7zRa7MhHG3vIlaE+nADqze/S9AK4THddLlzkJ3WpnQ7DUez8QzhMLi/HPMkO5OJ1ATsayvJmchfLv/PaPmlJRLj8ETHaY4v+2qn4cJhRK/rzxv2YbochHYcjZ6P9/diYhLcUmqHb+rPvtrm+CyfPR4y3V/2s+FIGE98fLQPbvzc1PdG+2Wr2fmPEOHzhn12XX5p8Ta7DphfOXd2nfA0/rciDUEsLCqDVZiN/fl53/8RRCI4DUe0XhsGCc74ZnXOF/aD88vxbzASJILFtR/Ns/Nhl5VpEKkJUBWqtvuKFf/9FD/OnIDhctj9nuEw7Lw2afhb9Hoy4732sQyvi3R3Gu290XvGprrdlN/KYBUJGdHrO9YRQyRiRa/vxnFb0/iyad+mvjUSsTDcTlqN6W+X1fLV++2wTf1GXbgOkj12XxT4yr1bU38QCFvRMYlhcN4PfoS/MnrM8mAFViRit3NN6W4qQ5K9ze4t/FbArgNN+afKj2EY9rgvHAnjcTns732WD6/p/bK+WaFovSmpJsYTbZNiPS4sX7QtMFvFcfTzCnxhPzGjukavfywiRKLXdST4ZRxYuDpkNju/RdOmcOBoHUash1L/ETzf64yFRZ/U3tH7KitaTlYkAoaB23RH/91UFw0HSc5E0typ7G3YR6vE6D0cvuj1bGDiNb2097Zj0IXjovf5Df7o1R3jYVhBm2g+I0Ei1QHqfCG8Dg9WQ4B5D75LXbiOgf3aHnceU10pje1yUvQaCje2aY1jitb/NaZZuceYsdH+3B/6sj21QhhOB70Te9r1GCDeEcea4g8IRkL22NTCYlFoMXsb9hEuqSEcCdPmhcuxIhHMVrH2s4qm+26Av//2UyDafgFYB2rs6zRohYhgYRoG5RXRtq1pnBSIBAha0Wvb8Dij5R22ovUqEmG8cwxxjjj8H38OwIqfzcNlRvuRoBXEZTiJ+EJ8NnNBY9qb11kT0y4ne0zmPP5RbiQYvZbHO8eAL9TYIjdvj0xMIpHo/bc72QtOo9myxeE9FXa+8tolN+bTaNZO1IXr7HSYRMsnYAWi9cgZjcuKRIhxO6hovB/xWwEMt8tuWy0sGhr7iEhNgEWhxRiYJDkTeaTzNdE4rAhvrNjD4fL6ZuN7MzHWHss09esOw0EkGMZwRMdfTX2mx+UgYkWIdcTgNFzsqttjl2OtLwimwd9f/d2X4Rvjtb7WztnlEwnb6XYYDnzBL8slUOO389cUX4IzHsPloD5c3yyeskD0vtPR2E7GOeLset6U16/Wza+eg6Y0BSMhIr4gjlYJZLSKjeankd1PRCwiviD14QachsvOVzgS5u+v/DY6Lm48H189xyltE+2xZBO/FSAvrjORQIhUV0r0OdnBavyRaLvpbNcKDINFocXEOxvH8cEQeBwYKTH2WCgUCWOtOYDL/DI9ViSCVVmHrzJats8cW0SqO4WvOxo8ZtfPeEccViRC/2dGR8vDChK2IuAwiHXHEakJQNgi4g9RWvnlPaLlC0avFZfZrK91dkzHbwWo9QWJ87rgK2W+q6SKqlA1TtO0+xC36SYcCRNovAdzGS6OBsqjzycwMdyN5Wd92f5WBqvscWfTPuFImMP+0mhbWxHtu9buOALQ7JwaHif1gTDOjpl2/+rq2PisLBKMXpNOk4AVsMvVNAzmPfguEB0nN/VTTc84m9rJc348KPpcLTcV0zQwDZODvkPENI4vmu7xmp7lmS4H+30lRHzBaD/c2J43nfevaho3Nf07+g+LZ44tAqJjhARnfLQO11WS7ErC2T4peo/rNElPa/uVuL7sGyHar3z1GBF/iERnIjSek4gV4e699+M0Dbtv6N81g1ivKzoG8Tij+4XClAcrMJ0mrtwMu5ya0r3zwObGcg5xyS0D7eerZmIsVmO/8PdXf2eXeTgSxmlGn6UFG581+q2A/Xx6vHMMQStIJBy9T9teu8vOo93muKLHbmpvLCKkJn45NguHo/cOMR4nDjM6nmt940h+PvyF6H1MYx3wmO5o++swMQ0DI+HLvtM0DLv+AmR52lC9+xhU+PDc0Nc+VnlNdNxlxkTvlcY7x/Dz4S/YdaMiVEmp/wixHhf+QBh8Xz6HOFBWR6zXSbwjzu63jwaPRc9PIBqu3mrA4TD5+yu/pbIu2vdFfEEqg1XROmNF+9QL/343mF+O750eBy5n47Nw0/jyeabDbOyDnPxgUDYNjc9qDCAUtk74zKK+8TlSpPGaC0aifXpCTPRYTb8nvLu+BILHP+eq33gYp9sNDpNBF47DtMfk0XY+L64zuJo/m66pPGY/KydkESZaNw58sDbaljWWf8NX7qdMzGbPA0T+lWnSgoiIiIiIiIiIiIiIiIiIiLQIvR5CRERERERERERERERERETkTH1tpVI5OVppQURERERERERERERERERERFqEVloQERERERERERERERERERE5U1pp4bRopQURERERERERERERERERERFpEZq0ICIiIiIiIiIiIiIiIiIiIi1Cr4cQERERERERERERERERERE5U1oy4LSo2ERERERERERERERERERERKRFaKUFERERERERERERERERERGRM2UYLZ2Cs5JWWhAREREREREREREREREREZEWoZUWREREREREREREREREREREzpRWWjgtWmlBREREREREREREREREREREWoQmLYiIiIiIiIiIiIiIiIiIiEiLaLFJC3PnziUvL8/+GzBgABMmTGDFihWnFd/+/fuZPHkyvXv3Ji8vj+3bt3/HKf7HKi8vZ+bMmVx++eXk5+fTu3fvk953xIgR5OXl8cQTTxz33d69e+0yXrNmzSmlae7cuaeUjiavvvoq1113HUOGDKFPnz6MHz+eZcuWnXI8IiIiIiIiIiIiIiIiIiJnDbMF/85iLZp8r9fLwoULWbhwIY888gh+v5+bb76Z9evXn3JcTz/9NPv372fOnDksXLiQnJyc7z7B/0ClpaUsXbqUVq1akZ+ff8r7x8bGsnTp0uO2v/nmm8TGxn4XSTxpzz33HFlZWfz0pz+1J6fceuut/PnPf/7/mg4REREREREREREREREREfnn5mzJg5umSWFhof25V69eFBUV8frrr9OnT59Tiqu4uJh+/foxdOjQ7ziV/3/k5eWxatUqILrCwc6dO09p//PPP5+//vWvbNiwodnqCG+99RYXXHABixcv/k7T+21ee+01UlNT7c9DhgzhwIED/PrXv+aHP/zh/7d0iIiIiIiIiIiIiIiIiIj8f2MYLZ2Cs9I/1UIRmZmZpKamcvDgwWbbN2zYwKRJkygsLKRv377cddddHDt2DICSkhLy8vLYunUrb7zxBnl5eYwYMeIbjxEIBJg5cyb9+/enX79+PPTQQyxZsoS8vDxKSkqahXvyyScZPnw4+fn5jBo1iiVLljSLa/r06Vx66aWsWbOGsWPHUlhYyGWXXcaWLVuahYtEIrzwwgtcdNFF5OfnM3LkSF588cVmYUzzzE5FSkoKgwYN4q233rK3bdu2jb179zJ69Ojjwr/++utMmDCB/v37c+6553L11VezadOm//M41dXV/PSnP+W8884jPz+fcePG8eGHHzYL89UJC026devGkSNHTiNnIiIiIiIiIiIiIiIiIiLyr+qfatJCXV0dVVVVtGvXzt62YcMGrr76ahISEnjqqad45JFH2Lx5M7fccgsAGRkZ9usgioqKWLhwIc8888w3HmP27Nm8+uqr3HDDDTz11FNYlsXs2bOPC3fHHXewcOFCrr32Wn75y18ydOhQ7rnnHlasWNEsXFlZGTNnzuT666/n5z//OX6/n2nTphEMBu0wjz76KHPmzGHs2LHMnz+fH/7whzzxxBMsWLDgTIusmUsvvZS3334by7KA6Ksh+vXrR2Zm5nFhS0pKGDt2LE8//TRPPPEEbdq04aqrruLzzz//xvgDgQDXXnsty5cv58477+QXv/gFHTt25Kabbvo/V4b45JNP6NChw5llUERERERERERERERERERE/qW06OshAEKhEABHjhzhZz/7GXFxcUyaNMn+fvbs2eTn5/PMM89gNC6n0aVLFy699FJWrFhBUVERhYWFeL1eUlNTm71u4usqKytZsGABU6dOZcqUKQAMHTqUa665hkOHDtnhVq9ezfvvv88LL7zAeeedB0RfcVBWVsbcuXMpKiqyw1ZVVfHyyy/TuXNnAGJiYpg0aRIbN26kX79+fPHFF7z88svMmDGDK664AoDBgwfj8/mYN28eV1xxxRmvstDkggsu4KGHHmLNmjUMHDiQpUuXMnXq1BOGnTZtmv1vy7IYMmQImzZt4s9//jM/+clPTrjPkiVL2LFjB2+88QadOnUCouW3b98+nn32WZ5++ulv3G/Dhg3MmzfvDHMoIiIiIiIiIiIiIiIiIvJPSq+HOC0tutJCfX09PXr0oEePHgwfPpx33nmHxx9/3P4v8hsaGli/fj0XX3wx4XCYUChEKBQiJyeHNm3asHnz5lM63q5du/D7/YwcObLZ9q9/XrlyJcnJyQwcONA+ZigUYvDgwWzfvp1wOGyHzcjIsCcsAPaP+aWlpQCsWrUKgO9973vHxVVWVtZsssSZio+P5/zzz+fNN9/kk08+4ejRo1x00UUnDLtnzx5uvfVWBg8eTLdu3ejRoweff/45e/fu/cb4V65cSZcuXcjJyTkuL990Lnbs2MF///d/M27cOC644ILvIpsiIiIiIiIiIiIiIiIiIvIvokVXWvB6vbz88stEIhH27t3L7Nmzue+++1iyZAkZGRlUV1cTDoeZNWsWs2bNOm7/U/3Bv6ysDICUlJRm21u1atXsc0VFBZWVlfTo0eMb42ndujUAiYmJzb5zuVwA+P1+O65IJMLAgQNPGNehQ4do27btKeXj24wePZoHH3wQgPPOO4/k5OTjyqm2tpbrrruO1NRUpk+fTlZWFh6PhwceeMBO94lUVFSwbdu2E5aLw+E4btuBAwe48cYb6dmzJw8//PAZ5kxERERERERERERERERE5J9Yiy4ZcPZq0UkLpmlSUFAAQM+ePcnNzWX8+PHMmzePGTNmkJCQgGEY3HTTTSf8r/S/Pvng/5Keng5Ef3zPzMy0tx87dqxZuKSkJFJTU5k/f/4J40lNTT3pYyYlJWEYBq+88oo9oeGrcnNzTzquk3H++ecTCoV47bXXePzxx08Y5tNPP+Xw4cP88pe/pGvXrvb2mpoaezLGiSQlJZGXl8ejjz76f6ajvLyc66+/nlatWvHMM8+cMO8iIiIiIiIiIiIiIiIiIvLvrUUnLXxdQUEBo0eP5rXXXmPatGmkp6dTWFhIcXGxPbnhTHTu3BmPx8OyZcua/Vi/bNmyZuEGDx7M888/j8vlahbudAwaNAiAyspKRowYcUZxnQyPx8PNN9/Mpk2bjnvtRROfzwfQbCLB+vXrOXDgQLNXXXzd4MGDWbFiBRkZGc0mfXxdXV0dN954I8FgkN/+9rfEx8efZm5ERERERERERERERERERM4OhmG0dBLOSv9UkxYAbrnlFpYuXcpLL73E3Xffzb333svkyZO58847GT16NImJiRw+fJhVq1Yxbtw4BgwYcNJxp6SkMGHCBJ577jk8Hg/dunXj7bffZu/evUB05QeAIUOGMHz4cG644QZuuOEG8vLyaGhoYPfu3ezbt++kVhpokpuby1VXXcW9997L9ddfT69evQgGg+zdu5c1a9bw7LPP2mHffvttAHbv3k04HLY/FxQUnNIrJKZMmfKt3xcWFhIbG8uMGTOYMmUKpaWlzJ0791snIgCMHTuWV199lUmTJnHdddeRk5NDTU0N27ZtIxgMctdddwFw2223sWPHDh599FEOHjzIwYMHmx1bREREREREREREREREREQE/gknLXTo0IFLLrmEBQsWcNNNN9GnTx9eeeUV5s6dy/33308wGKR169YMHDiQ7OzsU47/rrvuIhQKMX/+fCzL4sILL2TKlCk8/PDDJCQk2OHmzJnD/PnzWbBgAQcOHCAhIYHOnTszbty4Uz7mAw88QG5uLgsXLmTevHnExcWRm5vLxRdf3CzcHXfcccLPs2bNOq3jfpO0tDSefvppHn/8cW655RZycnKYMWMGzz///Lfu53a7+e1vf8vcuXN57rnnKCsrIzk5me7du3PllVfa4VauXAnAfffdd1wcO3fu/M7yISIiIiIiIiIiIiIiIiIiZ7cWm7Rw2223cdttt53wuyeeeKLZ54KCAubPn/+t8b3xxhsndVy3282DDz7Igw8+aG+75557aNu2bbNJC263m2nTpjFt2rRvjOuxxx47bltiYuJxP8wbhsHEiROZOHHit6btdH/Qf//997/1+27duh0X97Bhwxg2bFizbUVFRc0+n+gcxcfHc//993P//fd/4/E0MUFERERERERERERERERE/u3o9RCn5Z9upYV/tLVr17J+/Xp69OiBZVksX76cJUuWMH369JZOmoiIiIiIiIiIiIiIiIiIyL+Vf7tJC7GxsSxfvpxf/epX+P1+2rZty/Tp07nmmmtaOmkiIiIiIiIiIiIiIiIiInKW0kILp+ffbtJCfn4+r776aksnQ0RERERERERERERERERE5N+e2dIJEBERERERERERERERERERkX9P/3YrLYiIiIiIiIiIiIiIiIiIiHzXDL0f4rRopQURERERERERERERERERERFpEVppQURERERERERERERERERE5ExpyYDTomITERERERERERERERERERGRFqGVFkRERERERERERERERERERM6QYRgtnYSzklZaEBERERERERERERERERERkRahSQsiIiIiIiIiIiIiIiIiIiLSIvR6CBERERERERERERERERERkTOl10OcFq20ICIiIiIiIiIiIiIiIiIiIi1CKy2IiIiIiIiIiIiIiIiIiIicIS20cHq00oKIiIiIiIiIiIiIiIiIiIi0CE1akLOK3wqQ5W1De287klwJxDniCIcjWFhcdUFnBvW5GL8VAKAqVE04EgZg4odzAXCbHsY7x5DpySBkWZiJMQB4zjuHtAQPVuP/4hxxXNS3HQXJBWyr3WEf32W4qAvXMd45hvYdWzF2VFcyPRkA1IcbcJtuAH6y5U4ceamYiTEEI0Em/O0GsmPaA9ArsYDsmPb4LB/BSJBNNVsBCIYtFoUWkxSbSnxyCsOuu84+blKci06xHfBZPtbs/Ft0YyRCTaiWtmlxAFhYfPjmQurCdTgMB/XhBtp72+E23SS7ksiMyaCdN4sYRwznjb4CCwuAdeWf4GkMc+vDF+I8J40kZyKvX/QTDMPg49K11IcbWBRazNZ9FUz8cC6764tJcaVEy/TCTvgsHwCxrVqxrXYHK//2GgWJPTANA8NhEp+cQn24gRsnFNI9viv14Qbe/q93CUfCVAarGHb1ZHyWDwsLZ+d0qkLVpDbGf9B3CFen1nS9cyD7fQeIj3Wx5Pv3Uh6s4PXv/QSAZFcS9eEGANrHtAUgMdZFdkx7Ox46JNthXYYL0zAIBQLEOWKjdcB0E3/vULJj2lNVF8QwDNLcqcQ54khyJlIbrvvyWIE6BnQYRvyIHDLd6TSEG3Ckx9EQruf8nlkErAAdYnMwvjKdLvvCTnga60eyK4mGcANBK8Smmq24TCcJznjM1FgchgOA0oYj+INhxjvHkO5O42ignLy4zsR7nbRyp+IyXdH6H4FYrxPcLoKRID/ZcieLQovZsnstWd7WJDkTSYyPlkEEi1J/GeFImNpwHV7Ti1Vdj8NwEApEr5u6v2/H2ZgGq6YBh+GgZ0IPctp2BeC8sRNo581iYPeRhCNhfJaPWEeMnbeaUA0/2XInvmPltHKn4mzfijR3Kj0TelAfbsBluPBZPg76DvPGxXfZ16vX9FIVqsablmKXWZsu3cAwSHDG4zJd5Lfvh2kYxDljCUfCJDgScJkuDvoOEe+Moy5cR5e4jsQ6YvjwjVfxml67DQAoCxzlq8KRMBEsIoEQgc9LSXWlYDZ2ixYWKz94nV11e/jhb36IVdVAnNdJujcdrAhEIoQPVtLOm0VlsIpFocX8/ZXfApDmTgXTYFCfi6kJ1QJw2F/KeOcYfJaPcCRMnCMOC4uqUHVjudWS5k6lPtxAXlxnzMa6k+nJINBYRgM6DAMgzhmL23QTjASJcXj445vbuW3DL8nytuGyF8YSjARxGa7o+QzXY2LSzptFujuNdHca/bMGEueII9YRQ+uUtmyo3hSN1xFtS6pC1TgMB34rgNfhYV3F+ujxOxVx5EgtdeE6rIYAA3t9j/o95Vhhi0xPBjX1QRaFFuMynPz5gh9jGAYBK0CSMxEjrxWl/iMAmIaB02HgC/sJRoLRk9EQwmf5CVgBDNOkPhyte4tCi1kUWhwN4zRJc6cS64jBb/lxGS48pps4rxOv6aV/1kD8VoDqugCkxxLBIsWZbJ9rn+Wz2yq/FbDbCqfbTbo7DUfrxOi5r6zDwsKRnUR7bzt731RXCsGGIF7TC4BhGAQjQdp5s0h0JRA6WE52TPto3N8bQjtvFpFI9Bx3iM0Bov1EQ7iBymAVvrDProt+K0CKKwmABEcCwUjQrrte00usIwaH4bD7NZfhYn9DCSW+g/a1ndA2mv6msHGOOAKWP3pO64K09mSS5EqkfdeCZtdBrCOGtr0LIRKhKlRt10mv6aU6UMWnD74PwKjRXe3tViRCXbiOBGcCgH39W1hkutNxGA47z1/34dt/IMEZT6YngyRnInHOaBscH5OEMyedGycURuNMSsCREk/NZ1/Q2pNJXlxnO45BfS4m1hHDsf1V3DihkCxvG5JcidE623h+NtVsxevwkuVpQ02oljhHHHGOOOrDDWR6Msj0ZNAlriPJjeV+wxW9IBIBYHvtLrK8rRl29WRqw3W4DBfeUV1xGi4SnPH4rQBWnZ84r5Msb2u7Hic5E+xrD8CqasBpOKiqCxD+vJKjgXIAMtxpOAwH/XOG4jHdWL4gZscUHGkJvPVBMf2zBjL0yknNys3jiSHZmczHpWtxmdGF0sKRsH1dpSdHxzN1jX2V1ZgXgPyE7qxatYSl81bbfYzfCpA44wLaeDLZdvMvAezxRKQuyPbaXThw0CuxgH6pfaPXMSbd47sS39hWGA4HsY4YwpEw6e40FoUWk+CMJ9WdbB87zhFHMBKkQ2wOLsNFt/g8TExaezKxsDDc0eu4PFhBv9S+FJdGx1zezHjqww32+emX1JtQODpuSXWlEI6E+XDJq7x//cMErRBxjji7vQ1aIQAO1/w/9u47Posi8eP45+lPeiGdQAgtdAKGLkbAXpDzFOVEUFE6oiKK9VBRPBUVIh6iUUGleWeBO09PLKAgIIIooCCEACGBBEJ6nv78/nhgvSgqxftx3n3fr1desruzszOzs7Oz+4yzJXiDPoK1oevUaXYQDAZDbfi/1FsI9R36nP07ghVuY501sxGugIv97gPU+muJtcUQbgnDZAm1j66AC39JDU6zk5Uf7DDqQZ3bhyUjmnp/PTvqCsBkIiuiFf7DtaH2r02jBvcmEyb8Qb/RX6n11RrbbF3TCBCgbWRrkh2JtGybgzfoNY4fKK8lSIDGzjQcZjvWMBt1/nqCNR4OuEuJskaSGZaBO+ChS0wnzNFhVHgrAciKaEVcpJP6I+2id/N+LJZQ3YqwhmN1huqyxWQhWOsmyhKFx+0i0Z4A/gApjmQAmoc3C5X9kXJNtCcY7ZDJbCIQDBIMBnEHvi9bgGAwSMvw5jjMdrIiWxJvi6N7s76syHuOuAu7EmWJxBxmx2qyYL/g++s/zBLG7rJaoy5XbwldA2nOVADjPh5mCSPZnkjb7DRWTJtFy/DmxvXptITaicat2hIggBkzNf5a7Gb7kWvIROuIFpijw0l1JOMP+om2RhNuCaPOX0+iPQF/0G/0lwCj7YmyRuIP+o266w/6CW/ZGH/QbzwzuAMeLOZQm5ndqDOJ9gRMNgsW85E+BJDkSKDCW0mFtxJ/0E+dv97Im93soHVEC7x+Lya7jXhbHOWew9gsZmqPtFkmk4l2nXpjMploGdGc8xc8xIAX/4g/6MeMGafZicNsx4TZuKaiMuNItCcQZYkChwWb2UrQH8Ab9BIgELpHO6zkxHWle3ovWkW0oE1kFuefkW6U+dHzYjFZjHoeYYnAkhiN61C5ce9LiWtMoM6DzWQjcOSZ5uYvQ23Rmi3LjTTVVVcZcdb764m0ROAN+OjV7SJ8dV4syZFYTBZWrXyLCGs4lqaxmE0mHJGReAIeBlsHYjPZCLeEkRPXlUR7Agn2RqFzU+8z0lnpq6K0otgo4yhrpLHNH/Sz330As8lk3LcOuEvpkdUPm8lGkCDDB7YLXRtgPGOlOVN4+sy5oefH0hojH06zk131u6nz1xNmcRAoq8FsMWMxWYh3xBMoqwNCzwsmi5lwS1joGTPGYdQpf9CPO+ChrLQGf70v1MfOSgtVRrOJQJ3HqJsWQv2paz7JA4sZs8mEJT0Gk9lMjDW6wfOSvUVKKIq4sO+v1Vo3mQkt8eNvkL8Ya7TRny0uLgAw0uowO7C3TzeumShrJN6gl3h7LGddO/xIPEEqKw/xyYL5RFjDKTxQTY8uaaH2JDmC1hEtiLFGkxmWAS6/0W8IM4f6DUevp0BlqM1sZGsElW6ueH4QJkuoH51oTyDM4sDhDDfyE2WNxGwy4TQ7iW0RT6WvigABbGYbVpOFGGu00VaYMYHDErrnWyOItESEnssqXRS5iqk60mcudpeQGd6UjLAmNG7WOlRGgSDVdV7aRGZR7/ZhspjxBDwE67x8cP3UUJ80IvQ8ZzFZjL/m4c1CaQoGiLJEsWrlW6HzcOQeiC+ACQjWuUPvF9x+LCYLBdUFBIJBmoalk2CPD12/Lh/hltD7iKPvImwmG7vr9+I0O0P9mUCQKGskWM3YzXbMJhPpzjRSE5pgjnWG2siYCCwWK4Hqery+gBGPZ0sxkWE2qrzVAIx76FwywzL4Y+Zwo32MsERgDnNQ76+nZUQm1iP5NNmOtJ8VoTZh3B25VHgrmT3tQ2Ks0RzyHqJDVLtQfSYQev4ggK+4nK+qtxjXkyfgodhdQrozjUpvVageEOpPQ6i9xWIiISKRpRfdjjfoxffdIVpGZBrP90eteGgmpvDQM9bRNj3NkYo/6Kdxs9Yk2hPwBnyYLWZSIlNwB9xEWSOp8dVS568PtZF2KwECBP0BIqzhBF0+lviW4g/6cfbLAqBHq7MJd1rxB/2Uew/jyEgGs4lWT93A02fOZVPV10afBiDJkUjQ4zOu/1DG/cYzIoTaXNyhbUt8S8FsItGeYPQZj76n8ga92K0OYqzR1M5aCy4/Qd/3fRIcVmym0D67S6tpGd6cNEcqroDLaB/TnKnGNVLnr8cVcBFhjQj1q1x+47zUuf1GvzRIEFO4nQhLBFHWSKKskcYzhyUzFsB4Vut7xTUAOO0Wrr2wDW2axhntToQlAnNsOGWeg8b+LcObc0bj7uD2EwwE2e8+QL3fTbwtjoOVLoJuDxW+Smr9tXRv1he72U5GWBPsVgvm2HB6thtgvJMItV92XAEXac5Uo10/KtwSZtSNOFsM4Y7vJy++8vwsLCYLkZYIo7yT7UmYI5xG3/Soo2n3B4LYzXZ8QS+WuEhyYroQG5PYIKw74CEQDBppPNqPc9rCCByuIVBdH3p/BUZfLBgMhu6vBDFHObGZrYRZHPiDofYi0Z5A7uOTSXYkEmMLXSv/+gxjMZvAajLy4A54MGOm5WsjjHMVYYlg9Zq/UewqIcYaTaCizqinUbGh69Ac7gBPADw+WoY355CnHE/Ag7lrCu6Ah3h7HG26hPq61iaNCPoCmJMjcLl9oWccsxniwrDaj7xHs8ZywF1KhCWCSl8VnoCH8ppQ/9JisoTSvfMw9vbpBOo8mGPCqamvpNblM86lyWIOXSv20Lk6Wkc/XbaICEsEdmvo2Y1gkOgjZdMkMXRP8vj8xrNwhDOS5uHNyGmdyGDrQGJtMTjNThLtCZhNZgK1obbNZLNgsn7fHsL370iOvjeEUJ/BeVmojUg6cg+2W7/vZ1pbJ1Dv9nLOS78jeOS+f/R8H30+xRegkb2R8UyyvaiCcQ+dS4ojmQhLBGnOFF5b/h0V3koSIhJJc6byydclxETYSHUkc/jjXQSCQer8dXRP60ndkTbl/IXTQnXO7CTBHo+vLnRPsTYNlenR+1NUbKPQvcYc6rscPS9Hrwff0fbLbsPl9hFvi6PCWxk6n7VeilzFpDqS8e078j7Y4wdzqB46zHbq/W6jLgYJGO/32kW2CbUR/mBonfPIdekLMNg6kEAQYm2xALx7z/sEg0HsVgf+0tA93JoWR+fojnjrvKxe8zfjXdzROmMxWbCkxxBvi+Wd2Wuo9tXgMDswx4aTaE+gzl9Pz3YDjDw6zHbMZhNmkwm3x49n1wEywzJIdSSTYI8PPTM7ojGZTaQ4ksm9eTQAnoCbGGvonY5nw24AUpyh560yz0GW3/fB9/XBYjbeN5uPlFGn4V1Y/cnbBAgY773CjryrDdR7aGRrhL+4Agi9M6j0VWP5l18FYzu0JLNHE2wdkmh3ViYQutbjo0L9T1/JYRrZ4+n7h2Gs/uRtIHS/SXOkHuljBDGZTAQ9/tAzN+D2+amsCbVdR+9HsUfe0R1Nf+SRd/K5j08mNsKO0+zEnBJF7oRRoesj2gEWM1/e9yHmaAeJjtB58Xv8VNd5jToSdiQe65E+YEVtqG04ej2YTCZMplCaoyyR+MuqjLw7zc7QfS4ldM23DG9uPMsBxu8J53ZNN473ryKyU7BmJmGODscc68RiP3LttmpEoygHxe4SLM7vr2d/0M9hbyWxtpjQbwdOm9Ff31W/m0AwiDUljqbOdM5I6BrayWYhyZFIRljTHx1f5L+RPg8hIiIiIiIiIiIiIiIiIiJyqvR9iJOimRZERERERERERERERERERETktNBMCyIiIiIiIiIiIiIiIiIiIqfIdIxPisgv00wLIiIiIiIiIiIiIiIiIiIiclpopgUREREREREREREREREREZFTpYkWTopmWhAREREREREREREREREREZHTQoMWRERERERERERERERERERE5LTQ5yFEREREREREREREREREREROkcmk70OcDM20ICIiIiIiIiIiIiIiIiIiIqeFZloQERERERERERERERERERE5RZpo4eRopgURERERERERERERERERERE5LTRoQURERERERERERERERERERE6L0zZoIS8vj6ysLOOvR48eDBkyhBUrVpxUfHv37mX48OF06dKFrKwsvvnmm185xf9e5eXlTJs2jSuvvJIOHTrQpUuX4963f//+ZGVl8cQTT/xoW2FhoVHGa9euPaE05eXlnVA6jnrzzTcZPHgw3bt3p2PHjpx//vnMnj0bj8dzwnGJiIiIiIiIiIiIiIiIiPwmmEyn7+837LTOtOB0Olm8eDGLFy/moYcewu12M3r0aDZs2HDCcc2cOZO9e/cya9YsFi9eTLNmzX79BP8bHThwgHfeeYdGjRrRoUOHE94/PDycd95550fr//a3vxEeHv5rJPG4VVZW0rdvXx555BGef/55fv/73/Pcc8/x0EMP/b+mQ0RERERERERERERERERE/rNZT+fBzWYz2dnZxnLnzp3Jzc3lrbfeomvXricUV0FBATk5OfTt2/dXTuX/j6ysLFavXg2EZjjYtm3bCe1/9tln889//pONGzc2mB3h73//O+eccw5Lly79VdP7c6677roGyz179qS2tpaXX36ZqVOnYrFY/t/SIiIiIiIiIiIiIiIiIiLy/8H0G5/x4HQ5rTMt/FBycjLx8fEUFxc3WL9x40aGDRtGdnY2Z5xxBpMmTeLQoUMAFBUVkZWVxZYtW3j77bfJysqif//+P3kMj8fDtGnT6N69Ozk5Odx///0sW7aMrKwsioqKGoR78skn6devHx06dODCCy9k2bJlDeKaMmUKl1xyCWvXrmXQoEFkZ2dzxRVXsHnz5gbhgsEg+fn5nH/++XTo0IEBAwbw8ssvNwhjNp/aqYiLi6NXr178/e9/N9Zt3bqVwsJCLr744h+Ff+uttxgyZAjdu3enW7duXHvttXz11Ve/eJyqqiqmTp3KmWeeSYcOHbj88sv59NNPf3G/2NhYfD4fgUDgxDImIiIiIiIiIiIiIiIiIiL/tf6jBi3U1tZSWVlJenq6sW7jxo1ce+21REVF8dRTT/HQQw/x9ddfM3bsWACSkpKMz0Hk5uayePFinnnmmZ88xowZM1i0aBE33ngjTz31FIFAgBkzZvwo3MSJE1m8eDHXX389zz33HH379mXy5MmsWLGiQbiysjKmTZvGiBEjePrpp3G73YwfPx6v12uEefjhh5k1axaDBg1i7ty5/O53v+OJJ55g4cKFp1pkDVxyySW8++67xsCAv/3tb+Tk5JCcnPyjsEVFRQwaNIiZM2fyxBNPkJqayjXXXMOuXbt+Mn6Px8P111/Pxx9/zC233MKf//xnWrRowahRo445M4TP56O+vp7169czb948hgwZgs1m+/UyLCIiIiIiIiIiIiIiIiIiv2mn9fMQEPphG6C0tJTHH3+ciIgIhg0bZmyfMWMGHTp04JlnnjGm02jdujWXXHIJK1asIDc3l+zsbJxOJ/Hx8Q0+N/FDFRUVLFy4kDFjxjBy5EgA+vbty3XXXUdJSYkRbs2aNXz44Yfk5+dz5plnAtCnTx/KysrIy8sjNzfXCFtZWcmrr75Kq1atAAgLC2PYsGFs2rSJnJwc9uzZw6uvvsoDDzzAVVddBUDv3r1xuVzMnj2bq6666pRnWTjqnHPO4f7772ft2rX07NmTd955hzFjxhwz7Pjx441/BwIB+vTpw1dffcWbb77Jbbfddsx9li1bxrfffsvbb79Ny5YtgVD57d69m2effZaZM2caYX0+H+3btzeWf/e733H33Xf/GtkUEREREREREREREREREfnP8x81ZcBvx2kttrq6Otq3b0/79u3p168f7733Ho899hjNmzcHoL6+ng0bNnDBBRfg9/vx+Xz4fD6aNWtGamoqX3/99Qkdb/v27bjdbgYMGNBg/Q+XV61aRWxsLD179jSO6fP56N27N9988w1+v98Im5SUZAxYAIwf8w8cOADA6tWrATjvvPN+FFdZWVmDwRKnKjIykrPPPpu//e1vfPHFFxw8eJDzzz//mGF37tzJuHHj6N27N23btqV9+/bs2rWLwsLCn4x/1apVtG7dmmbNmv0oLz88F1arlb/85S+89tpr3HXXXXz00UfcddddK5gANgAAy9NJREFUv1peRURERERERERERERERETkt++0zrTgdDp59dVXCQaDFBYWMmPGDO68806WLVtGUlISVVVV+P1+pk+fzvTp03+0/4n+4F9WVgZAXFxcg/WNGjVqsHz48GEqKioazBTww3hSUlIAiI6ObrDt6OcP3G63EVcwGKRnz57HjKukpITGjRufUD5+zsUXX8x9990HwJlnnklsbOyPyqmmpoYbbriB+Ph4pkyZQlpaGg6Hg3vvvddI97EcPnyYrVu3HrNcLBbLj9Z17NgRgJycHNLT0xk3bhxDhw411ouIiIiIiIiIiIiIiIiI/Lc4+uUAOTGnddCC2Ww2fsDu1KkTmZmZDB48mNmzZ/PAAw8QFRWFyWRi1KhRnHPOOT/a/4eDD35JYmIiEPrxPTk52Vh/6NChBuFiYmKIj49n7ty5x4wnPj7+uI8ZExODyWRiwYIFxoCGf5WZmXnccR2Ps88+G5/PxxtvvMFjjz12zDBffvkl+/fv57nnnqNNmzbG+urqamMwxrHExMSQlZXFww8/fMLp6tChAwB79uzRoAUREREREREREREREREREQFO86CFH+rYsSMXX3wxb7zxBuPHjycxMZHs7GwKCgp+lR+6W7VqhcPhYPny5Q1+rF++fHmDcL179+aFF17AZrM1CHcyevXqBUBFRQX9+/c/pbiOh8PhYPTo0Xz11Vc/+uzFUS6XC6DBIIoNGzawb9++Bp+6+KHevXuzYsUKkpKSGgz6OB5ffPEFAE2aNDmh/UREREREREREREREREREfhM008JJ+Y8atAAwduxY3nnnHebNm8ftt9/OHXfcwfDhw7nlllu4+OKLiY6OZv/+/axevZrLL7+cHj16HHfccXFxDBkyhDlz5uBwOGjbti3vvvsuhYWFQGjmB4A+ffrQr18/brzxRm688UaysrKor69nx44d7N69+4RmGsjMzOSaa67hjjvuYMSIEXTu3Bmv10thYSFr167l2WefNcK+++67AOzYsQO/328sd+zY8YQ+ITFy5Mif3Z6dnU14eDgPPPAAI0eO5MCBA+Tl5f3iQIRBgwaxaNEihg0bxg033ECzZs2orq5m69ateL1eJk2aBMA111zDueeeS/PmzTGbzWzatIkXX3yRvn370qlTp+POh4iIiIiIiIiIiIiIiIiI/Hf7jxu00Lx5cy666CIWLlzIqFGj6Nq1KwsWLCAvL4+77roLr9dLSkoKPXv2JCMj44TjnzRpEj6fj7lz5xIIBDj33HMZOXIkDz74IFFRUUa4WbNmMXfuXBYuXMi+ffuIioqiVatWXH755Sd8zHvvvZfMzEwWL17M7NmziYiIIDMzkwsuuKBBuIkTJx5zefr06Sd13J+SkJDAzJkzeeyxxxg7dizNmjXjgQce4IUXXvjZ/ex2O/PnzycvL485c+ZQVlZGbGws7dq14w9/+IMRrkOHDixZsoTi4mKsVivp6elMmDChQRgREREREREREREREREREZHTNmhhwoQJTJgw4ZjbnnjiiQbLHTt2ZO7cuT8b39tvv31cx7Xb7dx3333cd999xrrJkyfTuHHjBoMW7HY748ePZ/z48T8Z16OPPvqjddHR0Wzbtq3BOpPJxNChQxk6dOjPpu2H+x2vDz/88Ge3t23b9kdxn3XWWZx11lkN1uXm5jZYPtY5ioyM5K677uKuu+76yeP90nYRERERERERERERERERkf82+jrEyfmPm2nh323dunVs2LCB9u3bEwgE+Pjjj1m2bBlTpkw53UkTERERERERERERERERERH5n/I/N2ghPDycjz/+mOeffx63203jxo2ZMmUK11133elOmoiIiIiIiIiIiIiIiIiI/EaZNNXCSfmfG7TQoUMHFi1adLqTISIiIiIiIiIiIiIiIiIi8j/PfLoTICIiIiIiIiIiIiIiIiIiIv+b/udmWhAREREREREREREREREREfnVacqAk6JiExERERERERERERERERERkdNCMy2IiIiIiIiIiIiIiIiIiIicIpPJdLqT8JukmRZERERERERERERERERERETktNBMCyIiIiIiIiIiIiIiIiIiIqdKMy2cFM20ICIiIiIiIiIiIiIiIiIi8j9q586dXH/99WRnZ9OnTx8ee+wxPB7PCcXx8ssvk5WVxahRo074+JppQURERERERERERERERERE5H9QZWUlw4cPp1mzZuTl5XHgwAEeffRRXC4X999//3HFUVZWxuzZs2nUqNFJpUGDFkRERERERERERERERERERE7Rb/HrEIsWLaK2tpZnnnmG2NhYAPx+Pw888ACjRo0iOTn5F+N4/PHH6d+/P8XFxSeVBn0eQkRERERERERERERERERE5H/QypUr6dWrlzFgAeDCCy8kEAiwatWqX9x//fr1LF++nEmTJp10GjRoQURERERERERERERERERE5FSZTKfv7yQVFBTQvHnzBuuio6NJTEykoKDgZ/f1+/089NBDjB49mqSkpJNOgz4PISIiIiIiIiIiIiIiIiIi8hs2YMCAn93+wQcfHHN9VVUV0dHRP1ofExNDZWXlz8a5YMEC6uvrue666447nceimRbkN2NE0hDySxfSOLIxGWf34k9Fs5lV8gJmt5f80oVUl9diSYqie3ovAJb4ltI8vBkjkobQr3UCI5OHcvOOu8kdO5K82hf4Zk8Fn335HqOTh3HVuS35dPBC+gz4PeGWMFpkdeHemFuxNU1giW8p+aULqfBWkuhIoHVEC5o40znvjHReGfgqFpOF6vJa8ksX0j65I1ObTmaI7XfEDmhOoz/2I790IQv7vYAr4OaeJrcQ0aYp9+9+jPzShdhMNrqn9eTPrR4jIdrJY4lTOVx7iFEbbqbt2G44opxExUdwdqc0GjVuSrozjb5/GEZ1eS0j8y6l2ldDk0g7M9o/xVk3jSDGGk1+6ULOnDyG3j0vYeqex3m6+Hnm1r8CJhMbK79iVskLXP/SIDrlns+WvRs45+Wp9LxjJO2vuIR31+9lxJtDAOiW3B2L2RSKb9AQnmg2nbw2t9CvdQL5pQt5eO/TLNtYQuEzSynzHMQX9DNq3VijvOwR4dhMNm5aeROjNtzMEt9SrncM4e6y6eQ+czdBb4Au0Z3IL12Ie9Uumoc3o3efgQQO1dE2sjUPVc4gKj4CgKLV6zi3azqP7J3Jk23G0rvnJXRLyCHcEsbcPs8xp34evbpewNXWQVhMFl4etYzHUx/ijl0P0iQsnee6PUPt/e8Rbgljxr459LzqasIsYYzfcReNopK4LW0UXTqezZCLsrir8GH2PbyS/AUbSZsxhEOecp53vYrZZOb5AS/S7M7fM6ngj0zafjvlD35MhbeSZ/fPo+r2Zdy5axrV5bU8W7GQR6tmcUbTnsyes4a5fecyv8948kpe5MWrXqfz9Vfy7P55BAnQNrI1XTqezdPFz3P9i4Pocs5FPHP9X5m653FiIuzkly5kdt2LRFkjSbm+H/nZk5ld9yJpjhTaJXXgnvhxzO9yN5v2rCXeFsdtkaO53jGEWn8tjTOyeN71KphNPNvqT0yrfApvMHS9lHkOEm+PY/SmW5hV8gLjd9xFVHwEd5VPY+x3d3J3k4mU1uyne5dzuWzDZIIuDwDmKDt7XUWs2foBr3n/SlZEK9p0O5OOl1xME2c6/qCfmee+jDM2Bl/QS9XXOwkzh3PZhsnM9yzBH/TTPLwZjezx5JcupEfLXHr3vpR+H0yh1lfHyDVjmD1hGQ/H38OOb9az8/HXeWDPDDIzO/DVns8JBIO0Te1EQV0hU/c8zubqreSXLqTcc5jWES24c9c0Opx9LvmlC8lueybdErvxbKs/MbfPc3RL7MbcvnOJt8UxLuV6lviWYjFZuO2riYz97k4mF/8Ji8nCa96/kl+6kO5pPVniW8pjzW5hxFt/YF7v8RTXlzDib0PZee+r3PTRCHbX7+Wub18E4IoPn+b3HzxNvd/NsJt7EXdPLtW+GkYkDTHapPzSheSXLjTatQpvJc+dkceTxc/xp6LZ5JcuJK5lJv6gn3Ep19PE2RhXwMX8R1awtmAl+QNfY8a+OXR77jbSnWkc9JSz/ron6dsxlZZDL+S+tBvpltiNri37MC1jCo/snYnNbGWvq4jWvfvSqkcfzInRvOReSJtuZzJ60y3kly5k3d7VvOReyD1NbgEgOyGbR4vysJls5JcuZP6szxi5ejSDejShz1mD2P7tegCG3XAGxUNeo82tg7moYzLV5bU4+7YGwH+ohtc8b5IR1oRrf9cOgOe6zqLL2Rfxp0b3s6t+N1kRrbgtbRRrZ74EgDfg49rftSO/dCFnNO7OY4lTWb1lPy9e9Trdbu9N24svAKBd91w6xLTjFc9fuDfmVrq9ewujvpxIuCWMJ9qOAquZZ/fPI8oayfw/fkh+6UIS7PHYzXZeuCC0vkluT76u+JpvK76l3eM3cf38y3ks836sLULf5qpftplJBX80zlm1r4arz2uFJ+DBH/Sz0PsmAA/smYHT7GRd0Wc4LU5y/3wP1z9/GRaTha+qt5BfupDU3mfw+w+epmV4c17x/IXMsAxat+rKrJaP8Gzdy/S9/A8c9JQzImkIU/c8Tn7pwlB97fMcOeddSpOwdNIcqUYdatyiDeXew8wqeYHwO/oRm9WCQd3TGZk8lJfdiynzHGRWyQtYTFaeOyOPfQ+vpHn3njyydyZBl5ebU2/krvJpHNq3h0R7AresvInhj5yL0+xkiW8p1eW1NA1rzPbanVz/0iDmdH6aZslRbNv9Jf0+mMIjVU/Tu/el5NW+wFPdn8VutjO58VjySxeyseorsiJaEe9sxIikIdzT5BZevGIxD2bcwX1NbyM37y48AQ8P7XmSrMYdaZvehautgxi95TZuWXkTf37xc662DmLd3tV8/s3HbKv5Dl/QS8r1/TjzrrGs3nWYsDHdKagrxLNhP9c7hlDsKsGEiW7J3TnnrQeZ3HgsAI/snUm4LTx0DhzJPL7vWboldiOzTTatLz2XmMhGPLz3aUYkDaG6vJast4bzbKs/EW4J4/aCB1i/YAkFdYX0X/BHVsyaQ9Y9f+CBPTOIskZyR9lU5vUeT3q3MwD4U+a9HHCXkRXZCn/QT6uIFni+2cdBTzlv9prNpr8tI790Ia0iWpDSoT3hljB27NvMs/vnUX3wAAVPvYkpysEnv38Ye/dMJsy/gl5nXMjkxmOZkj6B0Vsn0bhFG/JLF/JNzXYA8ksX4jDbGZ08jAdSxzI6eRj5pQsZmzKcGGs0f2w6iVvSbqLRqLMB2Dfz78w98CqTS+4jv3QhVQ9+SJQ1kgRbPDOaP0CTSDuPN3mYmKs60Dy8GeXew5y7eiJjvr2dSl8Vkwr+yNaab3ne9SrzH1mBy1tPm8T2xj3l6PXQPCmLKekT+HOrxzhj2GDjGvAGvTR65DICBGjZ7ywywpowafvtNHam0aNlLpbYCA56yunWrh8jBnfGG/Qxt/4Vuqf3whPw4Kl2ATCnfh45cV3JfepOlviWcu/uR3l837Pkly5kdPIw5hyYz+jkYTS/7gI2VX3NdbMvps5fT3JSU5wWB5XbdtH3vgnsqCvg0aI8/hh7O8Wu/bg3FrLujddxBzyMSBrCp28t5Kwl9+IKuHh2/zzm1r/Chf+cjj2nKRkRoT6Za90OMsKa4Hp2Hf6gn1ktHyEtPpxh9/cjyhrJQu+bbN20ijt2PciaTf8k3ZlG5a1LebQoz7gPdMyMp2f7c7hz17TQfbjwYQIEGJk8lJiBWaQ5U4mwRBBhicC35yBFrmJy/3wPfyqazaFt3+EOeAi3hNE8vBkVC79m6p7HMXVNYYlvaajvGpdKfulCws5qQ87cgaE6En4dsalpLOj/AvX+euY/tZrPN3/I+sMbeKbldLpcfxUfDJnKyxPf4cybrsdXVknGBX3ZVPU1Fd5KAlX1ZDRty7Ot/kRC947csetBdj66hAf2zKDMc5CW4c05o2lPvji4gZZp7Xi+NHTvmtp0MiOShnBz6o20imqJxWThT0Wzub3gAUyYWVf4CQDXPXMxKX3PwHZ2Jk8WP4fnne3c0+QWfv/B06Q7G7P2kseo8Faybu9qxt2Ry91NJtI4sjHbdn9JgADV5bV07jmAjVVf8WK3W4ixRhMXlUDv8TcQFR/B/YcfZUabGTiu7kT3jD7MOTCfgrpCuvY5n2RHEjM7PMXwb6YyafvtjN9xF/G2OIpcxeSVvMi5rz5IsbuEtpGteXb/PF6++R3aRbZh9v6XePGq10l3ptE5uiOP73uW+5reRoI9nhvfHU7rnmeSV/sCI5KG0LPzeTyX9Tit0zoweuskDnrKWVf0Gc9lPU4gGKR7m7MJBAPM9ywhQACAFEcyYZYw7oyaQOO4pty5axqR2S0wx4ZT6avCG/RidntJd6ZxRrtcnj28iK82fcLcA6+yqepr0ls04g+XtCHWFsMeVxGugIs7d01j9v6XjPta0Bfgpq8fY+qexyl8Zim1vjrK9hVixswS31Li7XFs3fk55pgIzvzHDWA2sanqa6rLaxlmH0yYxUGSPYEXr3qdjVVfkV+6kKj4CLL7nsdnG95lR10Btf5a5j+xCpPFjMlpI8YWTa2/ljaRrXm12xSmpE/AaXZy565p9P3DMHbUFhBpiWD2Xe/RJrI1sbYYmnbPofrbQr679nmue/YS5hyYT/e0njxd/DzXzbqI85ZPpba6kjBLGEt8S8npeg6BYJBDrkOkOVP5ovJLiuu8fDJyOlaTxchfhbeS50tfo3efgbRN7USYxYE74CHWFkO3xG4cPPJM0Da9C/mlCxn5yUj6zr2LA+5SxoXfQLIjic0VW2gd0YKo+AierJnDiKXX0H/BHym5fRGRlgj8Xx6gzHOQJb6ldEvtEbr3L72GqiVbjDah5p9f07FHfzwBD+uK1/CyezGz979E3cMf8KdG94f6CAk5LPEtpXT823wycjoWkwV/eQ3PZc9kT/kuTE4bXaI7AbDXVcRg60B2jn6bUV9MoM5fz7dL3+OKs5oZz0OXf/owZszs2rKRx1Me5NO/LealG95idt2LhN9yFqZwB8WuEv6UeS+ZYRn8udVjdB7yO1IdySzxLSXOFkOAAON33EVBXSGP7J2JZ9Me8kpepIkznc7nX0xmWAbNU9uy8pV5TGo8Gpffxbba7zjrhht4uvh5miVHkd/uHp4sfg7XrM+4c9c0esybTFJqBrXPryav9gWyUjtQ5atiTrsZWEwWfrf8KdYf3sDE2OE4zHb8e6u4JelqNg6dyQsXv8LsuhdpndOH8Aln8uIVi5mWMQWH2U65t4L5niWsuPRBEuzxtI5oQSNbPO6AhyeLn2POgfm8PGoZ3qCPklnvsL5yIxYsdDznfFr3zeXiTin0bNOfls2zsZlsZIQ1IcwSjhkzlUVF5Jcu5NC7X3BRx2TsEeF81OcZRm+5jR11Baz64K/07jOQTlHtCeysYMx3d5Cc1JRiVwn+oJ9Hq2YRZY1ka823Rp/w4WZ3sf7wBsalXE/JKx8xvc0NjPpyIq6Am61zQv1Kd8BDujMNd8CD1WSjwlvJ8IfPwZGeSPeMPty/+zH+lBm6py3xLaXxw1eSX7qQxd3yaBPXlmFDOtH7lSnsrt9LmecgozbczLq/LiEjrCmfb/2IMdsms7NiBzavj+XflpHT9RzWFX7CorPmYjfb+aZqG9Pj7yUlqw05cV057K3kT43uJ0CAigMlJDVuRkx0Agc95fiDfrw7DzCp8WjG5V1Kra+OO6Mm0DK8OcPG9qBlYhYd0roQcWVXvpz6Akt8S1niW0rL8OaYIpws9L7JrJIXmNR4NB2i2pJoTyCjZw+m7nkch9nOpMajmbrncUaHDQdg4rvDGb11Eu0i2wCw+pO32VlXSIK9EY8lTmXn4Xqe6zqLJs50Rvz1agrqCul21ZWUvv0Zd+x6kG6pPbhp5U0c9JRz7+5H2f77uRRWFdKue+hZL8meQLwtjjp/PQSCzNg3h5vev54u11/FypdeYrB1IPM9S3Ct2M4Tzf/ItsKNPNZuBPmlC0lzpnLTBzew6oO/snrsY4xYeg1R1kgirOGMSBpC7t0TiLFG8/mBdbzx6W7OX/AQ05vdg7lVPCmOZEYkDcFistAtK5e6pV8RZY0MPaPd3IuIfqFnpVvSbiLaGsnY8OvIHTsSS6MoRm56EttZGXzy5gJGfjKSsSnDua/pbdzw2u95smZOqExyxnBX4cMc8h4CIMoaycs3v0PjqHRaRmTybP7nJHXpcOS9lpVn98/jkzcXGGn6a+5kKryVvPrWVg64S7GmxxEkEOrHPXsrac5U/hh7OyvynuO2yNFU+2roENWOz9/4KzPazCAsEODu6Ft4rsOTdInuxB+bTsJmtuLbX8mgfz7JfvcBAO4qfJhRG26mbulX3FH6R1wBF7NKXqB5ejsu7pTC4coyHtk7kxRHMvbsdPa6imh2yyByWzVixFt/YM3WD3CandzdZCLtmnblyeLnyC9dyEN7nqRlhxz+GHs7+YMWMDZlOHX+epqEpVNdXht6dm83gxFJQ7gtbRSBOjddG3Xh3t2PEggGmZYxha5/n0igqo5wSxg9O5/HiKQhjEgawhLfUiY1Hs2omMG4Ai56/flOigq+4Y5DD3DF5xOY23sOjyVO5eFmd5F76xhyZk6kc3RHJqTeQM/O5zE2/DrGfHs79e46Nhdv5Pz2SeS3eIgty/7BLWk3EW+PpWVEJmevmMiN7w6n5aKbaBaWQeMBPfEH/bTum4t/5V7uKZyOCTO//+Bp5hyYz58y7+X5s55nwVk303hYNg83u4vY1DTaxbXFZDIx/JJ2OHu2IBAM0iKrC20jW7PEtxRv0IutTQqfH1jHtfYrsKY3onuT3pQc3kvps/9k2IMDCBKgPuCibWQW3/5xPpurtxL32GUs7f0gGWFNuWXlTYwY3Jlhd53F7Wl/CD2PL91CweN/5duKbxmRNIR9rmJirNG4Ai5aprUj3h7HvN7jmdNuBo2dqeQ0iaHgpX8QdHkxOW3cunYMMenpLO57Gy3adg09U225jbqlXzHuljO5d/ejLPEtZbB1ILlP3Ykn4CG3VSPuTxvJuwPvCb13SexGdosEttfu5Lk2U/AH/XgCHuzZGdxTOJ0xcVcC4Al4SLDHM7vuRWp9tdy+804mNR7N5wfXc+Cbb7inSei928wOT7GjrgBv0Mvzrle5p3A68bY4mpzXh92j59E5uiONbGbm3/sBb+feTVR8BNXltdS/t5U3By3gwZbXcf1Lofeeldt2MSJpCE8XP0+Z5yCutTtJc6SQ+9Sd3JR0DT3bJjM9/l7GfPsY7dM6k97tDD4f9ATNw5tRWnuAcHMY7535GGekx7Cx8iv8W8v4c+aj7K3fhzkxmr/mTmZS49F8OnQ6U5tO5vZtf+b+3Y+xfsiTANz0wQ2ceeFgbvtiPCOShmBNb8T9ux+jfukWbCYbjyVOZc6B+bS5+Dyqy2t5eO/TzH92LbfvmMztaX/g8X3PYjFZyLxyQKgOuxaQOKQvw0Z2Iyw8kgmLrmLd7lVUl9fyZPFznPO3B4xnQavJRoI9HoCpFY8xY98cvDv20y25O76PdlNdXsuEBYPp2fk8Xh6QT7GrhBev+StBb4A1r29mzLbJfFnwGa95/8rE96/j5h13Y7KYyIpoRV7Ji0TGhRMTl0B1eS0t09rx7dL3uL3gAfbN/DsBArgDbnz7K41nujVbP2Bq08k4zHae3T+PxxtP5uni51lz/Rt8UfkljXO7k9q1Mwc95Tze5GHiZl7Gp++9zqza5xn35EXcljaKZpGZdB7yO14c8hdMUWHMbDGNVnddzVM5s8mrfYHhT17AE83/SKIjgZd6jWPz5tAU7XlXL+b3HzxNduPQ7wG5D08y3ulUeCsp9x5m0pZb2e8+wJoty6kuryXCEkHW4AsxubzcljaKF69YzIil17Dt5r+zfPgf6dc5jfmPhZ7LhtkHM6fdDL49tJXMtLa4PtpGVkQr/tzmCarLa6n11+IKuLF6fOS0TsT33SGutl/GCxfMo2ezODqkRHLQU843NdsZYvsd+1yh79tv3hw6t9trd/LagHz8K/dSXV7L7P0v8elbCxl239lEWaMYdsMZbNz4EebkCExnpJLZqxdT0iewa/hLtIoPw19axaxLXsERF819TW8LvZO0OHm5ax55Vy4KPes+/in1lXX8c3joHd5DlTPI/vv1DLYO5OVRy3AHQu+7b/5LqI0+7K0kGAxSXV5L3rWvU3v/e0xqPJrB1oEUbljP0jW7jba/uryW9664F9+eg6zZshzvlhI2/mEm859fz7ArO3BL5CiqfTVcc2lbRiQNYWaLabzm/SuNnanM2DeHR6tmcfBQMXG2GAZbB5LuTGPZ2fewfvtKit0ljN46ibl9nmPFY88QY41m7Hd3IvKf6tChQ8yaNYspU6Zgt9tPKS7NtCAiIiIiIiIiIiIiIiIiInKKTOaT/0zDqfqpmRR+SXR0NNXV1T9aX1lZSUxMzE/uN3PmTLKyssjJyaGqqgoAn8+Hz+ejqqqK8PBwrNbjG46gQQsiIiIiIiIiIiIiIiIiIiL/g5o3b05BQUGDddXV1ZSVldG8efOf3G/Xrl18/vnndOvW7UfbunXrxvPPP89ZZ511XGnQoAUREREREREREREREREREZFTZDp9Ey2ctLPOOos5c+ZQVVVFdHQ0AO+++y5ms5k+ffr85H533323McPCUY888ghOp5PbbruNrKys406DBi2IiIiIiIiIiIiIiIiIiIj8D7r66qt55ZVXGDduHKNGjeLAgQM89thjXH311SQnJxvhhg8fTnFxMe+//z4Abdu2/VFc0dHRhIeH06NHjxNKgwYtiIiIiIiIiIiIiIiIiIiInKrf4FQLMTExzJs3j4ceeohx48YRERHBFVdcwa233togXCAQwO/3/1vSoEELIiIiIiIiIiIiIiIiIiIi/6NatGjByy+//LNhXnnllV+M53jCHIv5pPYSEREREREREREREREREREROUWaaUFEREREREREREREREREROQUmX6Dn4f4T6CZFkREREREREREREREREREROS00EwLIiIiIiIiIiIiIiIiIiIip0oTLZwUzbQgIiIiIiIiIiIiIiIiIiIip4UGLYiIiIiIiIiIiIiIiIiIiMhpcUKDFvLy8sjKyjL+evTowZAhQ1ixYsVJHXzv3r0MHz6cLl26kJWVxTfffHNS8Zwuq1ev5tZbb6V///507tyZiy66iBdeeAGv1/uL+/bv379BWR79y8/P/39I+fF54403yMrKory8/IT22717N/fffz+XXXYZ7dq145JLLvk3pVBERERERERERERERERE5D+DyWw6bX+/ZdYT3cHpdDJv3jwASktLmTNnDqNHj+a1116ja9euJxTXzJkz2bt3L7NmzSIqKopmzZqdaHJOq0WLFuFyubj55ptJTU1l06ZN5OXlsXPnTqZPn/6L+59//vnccMMNDdalpaX9u5L7/+a7775jxYoVdO7cmUAgQDAYPN1JEhERERERERERERERERGR/0AnPGjBbDaTnZ1tLHfu3Jnc3FzeeuutEx60UFBQQE5ODn379j3RZPxHmDp1KvHx8cZyjx49CAQCPP3000yePLnBtmNJSEhoUJb/Lfr3788555wDwJQpU9i8efNpTpGIiIiIiIiIiIiIiIiIyL/Xb3u+g9PnhD4PcSzJycnEx8dTXFzcYP3GjRsZNmwY2dnZnHHGGUyaNIlDhw4BUFRURFZWFlu2bOHtt98mKyuL/v37/+QxPB4P06ZNo3v37uTk5HD//fezbNkysrKyKCoqahDuySefpF+/fnTo0IELL7yQZcuWNYhrypQpXHLJJaxdu5ZBgwaRnZ3NFVdc8aMf1oPBIPn5+Zx//vl06NCBAQMG8PLLLzcIc6xBCW3btiUYDFJWVnZc5fdzeT7evKxevZpLL72UTp06MXToUIqKiqioqGDixIl07dqVc845h3feeafBvh9//DHXX389vXr1omvXrlx55ZWsXLnyV0mX2XzK1UpERERERERERERERERERP4HnPBMCz9UW1tLZWUl6enpxrqNGzdy7bXXkpuby1NPPUV9fT1PP/00Y8eOZfHixSQlJbF48WLuvPNOMjIyGDt2LHa7/SePMWPGDBYtWsTNN99M27Ztee+995gxY8aPwk2cOJENGzYwbtw4WrRowYoVK5g8eTLR0dHk5uYa4crKypg2bRojR44kKiqKGTNmMH78eN5//31sNhsADz/8MK+//jqjR4+mc+fObNiwgSeeeAKHw8GQIUN+Mq0bNmzAbrc3KI+fEgwG8fl8xrLJZMJisZxwXh599FHGjBmD1Wpl2rRp3H777YSFhZGTk8PgwYNZsmQJkydPpnPnzjRu3BgIDRzp168fN9xwA2azmZUrVzJy5EjmzZtHjx49fjLNx5suEREREREREREREREREZH/JSaT5lo4GSc1aOHoD+2lpaU8/vjjREREMGzYMGP7jBkz6NChA88884xxYlq3bs0ll1zCihUryM3NJTs7G6fTSXx8/M9+IqGiooKFCxcyZswYRo4cCUDfvn257rrrKCkpMcKtWbOGDz/8kPz8fM4880wA+vTpQ1lZGXl5eQ1+UK+srOTVV1+lVatWAISFhTFs2DA2bdpETk4Oe/bs4dVXX+WBBx7gqquuAqB37964XC5mz57NVVdddczZBAoLC5k/fz5XX301ERERv1iOCxYsYMGCBcayxWJh69atp5SX0tJSHnroIW666SbGjRsHQMeOHXn//fdZvnw5w4cPB2Do0KFGHIFAgB49erBjxw6WLFnyk4MWTiRdIiIiIiIiIiIiIiIiIiIiv+SEBy3U1dXRvn17Y9lisfDss8/SvHlzAOrr69mwYQN33HEHfr/fCNesWTNSU1P5+uuvT+jH7e3bt+N2uxkwYECD9QMGDOCzzz4zlletWkVsbCw9e/ZsMHtB7969mTp1Kn6/35jFICkpyfiRH6Bly5YAHDhwAIDVq1cDcN555/0orueff56SkhJjxoKjampqmDBhAunp6dx6663HlbcLL7yQESNGGMtHB3icSl6aNWtmhD0qOjqa+Ph49u/fb6zbv38/Tz31FKtXr6asrIxgMAjQ4Nz+0ImkS0RERERERERERERERERE5Jec8KAFp9PJq6++SjAYpLCwkBkzZnDnnXeybNkykpKSqKqqwu/3M336dKZPn/6j/f91doTjUVZWBkBcXFyD9Y0aNWqwfPjwYSoqKn7yR/eysjJSUlKA0I/4/+roJyHcbrcRVzAYpGfPnseM64eDFjweD+PGjaOyspLFixcTHh5+XHmLj4+nY8eOP1r/a+QlKiqqwXq73W7kLxAIMGbMGKqrq7n55pvJyMggLCyMWbNm/ez5OZF0iYiIiIiIiIiIiIiIiIj8L9HXIU7OCQ9aMJvNxg/tnTp1IjMzk8GDBzN79mweeOABoqKiMJlMjBo1inPOOedH+/9w8MEvSUxMBEI/mCcnJxvrDx061CBcTEwM8fHxzJ0795jxxMfHH/cxY2JiMJlMLFiwwBgE8K8yMzONfwcCAW6//Xa2bNnCa6+9Rmpq6nEf5+eO/2vl5Vh2797N1q1bmT17doNz5HK5Tmu6RERERERERERERERERETkf8sJD1r4oY4dO3LxxRfzxhtvMH78eBITE8nOzqagoOCYswicqFatWuFwOFi+fDlt2rQx1i9fvrxBuN69e/PCCy9gs9kahDsZvXr1AqCiooL+/fv/bNgHHniAjz76iPz8fLKysk7puEf9mnk5lqMzLvzrgIx9+/axceNG4/MSpyNdIiIiIiIiIiIiIiIiIiK/VZpp4eSc8qAFgLFjx/LOO+8wb948br/9du644w6GDx/OLbfcwsUXX0x0dDT79+9n9erVXH755fTo0eO4446Li2PIkCHMmTMHh8NB27ZteffddyksLARCMz8A9OnTh379+nHjjTdy4403kpWVRX19PTt27GD37t08/PDDx33MzMxMrrnmGu644w5GjBhB586d8Xq9FBYWsnbtWp599lkA5syZw6JFixgxYgR2u50vv/zSiKNly5ZERkYe9zH/1a+Zl2Np3rw5KSkpzJgxg0AgQF1dHbNmzSIpKelXSVd9fT0rVqwAQoMhampqePfddwHo3r27ZmQQERERERERERERERERERHgVxq00Lx5cy666CIWLlzIqFGj6Nq1KwsWLCAvL4+77roLr9dLSkoKPXv2JCMj44TjnzRpEj6fj7lz5xIIBDj33HMZOXIkDz74IFFRUUa4WbNmMXfuXBYuXMi+ffuIioqiVatWXH755Sd8zHvvvZfMzEwWL17M7NmziYiIIDMzkwsuuMAIs2rVKgDy8/PJz89vsP/8+fNPaHDGD/2aefkhu91OXl4eDz74IBMnTiQ1NZUxY8awZs0aNm/efMrpOnToEBMnTmyw39HlUy0XERERERERERERERERERH573FCgxYmTJjAhAkTjrntiSeeaLDcsWNH5s6d+7Pxvf3228d1XLvdzn333cd9991nrJs8eTKNGzduMGjBbrczfvx4xo8f/5NxPfrooz9aFx0dzbZt2xqsM5lMDB06lKFDh/5kXK+88spxpf9YPvzww5/dfrJ56dGjx4/ycqzjderUib/85S8N1g0aNKjB8uWXX/6jQRLHk6709PRjpkFERERERERERERERERE5L+VCX0f4mT8KjMt/LutW7eODRs20L59ewKBAB9//DHLli1jypQppztpIiIiIiIiIiIiIiIiIiIicpJ+E4MWwsPD+fjjj3n++edxu900btyYKVOmcN11153upImIiIiIiIiIiIiIiIiIiGDSRAsn5TcxaKFDhw4sWrTodCdDREREREREREREREREREREfkW/iUELIiIiIiIiIiIiIiIiIiIi/8k008LJMZ/uBIiIiIiIiIiIiIiIiIiIiMj/Jg1aEBERERERERERERERERERkdNCn4cQERERERERERERERERERE5RSZ9H+KkaKYFEREREREREREREREREREROS0004KIiIiIiIiIiIiIiIiIiMgp0jwLJ0czLYiIiIiIiIiIiIiIiIiIiMhpoUELIiIiIiIiIiIiIiIiIiIiclro8xAiIiIiIiIiIiIiIiIiIiKnyGTSByJOhmZaEBERERERERERERERERERkdNCMy2IiIiIiIiIiIiIiIiIiIicIk20cHI004KIiIiIiIiIiIiIiIiIiIicFhq0IL8Z4ZYwAPbV7MPSt+kxw5jTo1hX9BlLfEsZbB1IlDWKXl0vAMAf9If+u/MwACXbD9Kj+VlYTBYAgh4f3h37qfPX4y+tBOCzL98z4o6wROAw2YkJj8d8ZJjUoQ1bqfRWGWHcNbXsdRWR6kjm7Qtvx1vjBuCbbesodpUQJIh3V6kRPsYWBcD6yo0Mtg5k/eEN2M12ABKinVS7fAy2DgTgcPFeLCYLnyyYD0Ct20eQAABrt33E+D9fhtPiBGDcI+dR+OUXDcpmffkXBI6EB1j1wV+p9dfiPVQPVjOfLHyFF3uOAyBAAJPNYoR1ffQte8oKKPcebhDn4YJD7K7fi8NsN8rXKK8/nkuUNbLBulp/LXabBeq9eLfsx+pwhM5bXASegIdARR3+/ZUccJeRd+UiALqn98Id8PDxV8UA1Pnr8e2vxONxYzPZOLRvDwAmq4WucdkU1BXyyZsL+LzscwDCmiSzbvcqqtwVRFujAfBu2Y/LHzo33x7ayvOuV6kr2Pd92Sz/KyktGxH0BXAHPQAUu0oA8H28G4DB1oF8t3kdviP5Xl+50dj/1Snv8WSnmbjKK1gx/hE271hHn36XA+A/UInvu3IjbHyPjg2ObQq3YYp1Gsc4qs5fj7+omlp/LTPPn8f6yo2UHN5Loj2B/e4DuAMe6vz1FLmKCbeEYcbM2m0fMdg6kM9L1nLYWxEqzya9AUh2JOE0O/ih2Q9/BMABdyk2k43vNq/D4/OzrngNKY5kVr4yjzp/PcmOJG6LHA1A1dc78W0vJcYWTcvw5kx8/zpKyvZQ6a1mc/VW9rqK8Pj8fL6tlIywJngCnu/za7Xg21dOUozTqC/j8i7FZrISbY02rvvCXVuItcXgD/qpPnzQqMtH99lVv5uY8HgAgm4fABu/WUlVXSjfQY+XwspdVBQVUemrItIazmDrQBLtCUY5f7v3MN6glyUrCwAoOxw654n2BADOe+0hvAEvAEWuUH20mCx0aRna7qrxUFVSZaS5dctGBAnQPLwZTrOzQTmbTSYywzKIsIbjr6prsK1yZyH+oD90TZlNNO16Bq6lW7GYLBzevB0ItWMl7gPE2+KM63LlCy9ixkzQ48N/qJpd9aG6ajfbQ9fNvsOs/uRtvt26ltc/KaDq653GMfsM+D0A8bY4uqX2YMPBDaHzc6StC+uUbIQN+vykOJIJ1oauoUOectzLvjW2f/q3xeTEdKFyd+ja3Fb7HQC5t40l6Pax6oO/Uuo+SLIjiW2139GmaTZOi4O0sFQirOFGPBWHS1l/eANWixn/gUoKD9Ti2VREnb8ek93K/vr9AGyv3cnCs24+Uh+i8Af9rLh7BgDORvG4loeO7w348Af9fLbhXdL69cAU68Qd8FDtqyGuTSIA1f4afHvL6TPg99jbNW5wXso8B4FQ+5jiSObd9XvplX0+AJ6Ah+bhzdhcvZXSya8DUO6tIOZIm7Nq+V+pKqkyzpU36MXaJJ6wJqFyNXdPA6BnuwHG8arqKqjdX0rVqq3U+euI/JeysabHEWuLAcAS6+CzL/4BhO6Ts2/5mxEuLDKKuooKVi3/Kzl5FwGw5tsPOeOGq4HQdZMUmcLsW/8OgCvgMq4Hb8BHy/DmoTzXhc51gq0RSTGhurz185UARN7Wm6yo1qQ5UwGwmWzU+mu5o/SPJDuSqPJV8eWq92k26XcUu0oYN6YXGWFNAFi3exXBejcpzlA5zL7lb4QnRNA1LpsoayROs5MIazgHPeX4i6ohMZz8HmPxvL2NJb6luD/YQa2/lj5n/444Wwy+ehfeGjdpzlSjbSisLQTgoPdQqIzG9Kbw203Uf/ANtbVVR+rNkbDTVvJF5ZdGvp1mJzHWaCx2C336Xc64u/uFzhdmBlsHct5rD+HetJt4WxxVvhqirJHU+mrpc87viU1OZf3hDSzxLWV90VrSHKHy+a52J599/k6Da/ebmu3sdRXx6d8XU+mrwr1qBwCfffEPnJbv28avvl0FwBLfUpb4lgKQ4kjGYrJQ56+nXVQbANwBD5W+KopcxSTaE6h77QuW+JZiM4cmWDt6jtd+9zFfVW9hj6sIV8AFwOHKMiw2i3Ee19z5PhBqGwBirNEMtg7EtXQrm6u38nnJWqPuHY13XdFnlHkOsr5yY+i8EboGevcZyM7J80h2JLF/5Rd4g6G2uqCukIqSYtYWrCTRnsA329Yx2DqQcHMozorDpZhMoUeWo/XMmt6IPXcv4tV/budfeYNe47/jnhlo3HtTM1uzq2QbKY5kttZ8y4qHZtI8PNMo/+bhzdhRV4A74MFishhlXPNhAXFH8j7YOpCaA9V8suRVDtSXUuQq5ovKL9lW+x2fffkeuX++x7im/zUtR9vR7mk92V67k4ixZxphBlsHhuLdU9wgHzaTjTNvHYW7yo0/6GdT1WZ21BWw/vAGHGa70c5sr91JRlgT9rqKqPRVs/KVeQD4/xFq3/u9ej+BI211sMbDpje2AnDQU87hkiL8+yvIfvAmfJ8XYzPZyL1tLOHZzdk2fxneoJdPFr5C4LCLLyq/5NO3FrLEtxRv0MuGrz5i7Xcf80Xll0x8/zojToCcuK6UeQ4SrPMQIEDYH7oa+drrKjLq1obDXxr3Uvj+XtE8vBkAn773Ou6/h+4tn33xD/a7D1BVUsXm6q0Uu0qwmWzGvSsQDIDJRIKtkdE2+vYcxGayYTfb8QX97Kvcy4q85wD4+KtiDpcUseKeGRSUfAPApcseA7cPEyb8h6pZt+WAkTa72U6puwyA94fej9PsZHttqIyDLh9ba0LpXPPx23xTs52Cul1AqO8YCAYBcG/azctvb2GJbyn+/RV8XrKWPftD13qZ5yDNw5vxeclayr2HcVzbhY1VXxnHd5qdVPmqMJtMHPQeYktpaFug3sP+b76h2ldj5LtZvzMJVNZS6/IZbUe8LY62TWKB0P3KH/QTYYkw4t9c/Q11/nr+fvkU5ne+F4BKXxXeoJeCukIsJguDrQOp84f6K9UHD7C7tJb1hzcY58sb9FLvd1Ptr8a7qwybyWbEv2fN51z2jydwmp3E2eIY98h5rCv6jMOfbeaAu5QlvqVEp6dR7j1MlDWSDlFtAfhkwXwcZjuVvipWPD6bva4idtfvxb15L5urtxrnAL7vswHs/uPHVPtqMJvMob5qMEiQALvqd/N1VegcHKx04Q16ibXFkuRINPIMsHrVUtbtXc1BTzln5t1JhbeSrw99bcS/rvAT49+xmXE4zHZcARebq7fiCrgw/eAVi8VuYXvtTip9VXz74QfEWKOZPXU5loRoo239ZNEr1PnrOVBfiqNJEqtXLSXdmUaffpcb/e3Pyz7ni8ovQ/8+uD6U5vIyvEEv/qCfNZv+SdAfoMZXy+HPNlPtq6HPWYNIcSTTvUlv3HtDz6Ax1mijT+M70k5tz1uLxWQhSJA91XuItcXw6d8WA7Di3idZu2MFFpMFb8CHxWQhbEBbTLFO4976VfUWow4evbcdrg1tM5tM+EuraWSP50DpHvr0u5wKbyUFdYUs8S1l5Ysvfl9WR57Ljz7f/fOa+yjbv4dqT+heYgp3UOmr4qvyr6jwVlC+eg9mzFT7aih2l/DpP5YAsN99AHNkqL9S8MU6ojqnsGrlW+yq34034OOAu5TbIkdT4a2k3u/GhJmtNd82qLefvLmAcs9httfuJMWRHHreLavh8NotoQA2C2u+/ZBkRyLhlnA2VX3NrvrdfFMTui8dbRc+L1lrnLcoaxRLfEs575Xfs712J5+8uSAUVetUEuzxpDvTeLLTTKp9NeTee3ODetQ9rSfpzjS21+7ksndD/dxiVwllnoMc9B7CZrZS4j5ApbeK/e7v269vtn/Out2rjPI9+uwT/CpUH9YVfWY8N7835F5yZ9zJee8/aIT/umqL8Zx/9NwWf1gAwSBOs5M1336IK+Ci1l+LK+Bix9Yv2Fa9HX/QzxeVX+IP+tlW+x2bCtZyuLIMM2ZsZiu+ehcV3koGWweSk96DXfW7KagrBELvVCyJ0YyfM4i2Wd2ZNeg1Iz1rt31k5M1msrG9didFrmK820NtQLG7hFRHspHe3y1/yggflZpC7v0TWeJbSrgljOi2maw/vIH5ne8l6Pax11UEQKuIlgTLXVT7awDYUx5q049eN1trvqXMcxCT3coDu+ZhMpmIskYy6L0n2VK8yTjetvnLOPPiq4wy/6Lkc8o8B6nwVtIhqh3w/TuqB3fNN/oNLr+bCm8lmWEZrHgkjyABYm0xJKVGEZ8ew466AupeXMu22u/IimgFwJYd6yioK8Qb+P790advL2Le0q0k2hOo8ddR46tj38vLWbtjBWEOK/V/+dq4T7gDHuN9B8D8zvdy+ZGys5psLPEtpcvsiQRdPj4v+5w99fvwvbUNkz3Ut9xdv/dIHY/kzEFD8Af9uAIuep19GQmtGmExWfj074tJc6Qy99UNjLmhG4n2BMo8B1niW2q8w9hTX0SMLZrDJaFz0ahJBpUHS7HFROIL+qnyVrOu8BPeOu82IiwR9DlrkJHmgrpCpsXdZfTbKg6E8rOjLvRs37RRJhuWvUUgGGT/rHeN/ZIdSXgCHuJtsUZ+jvpsw7t8U7OdnV+sxR3wEGuLYXP1VmP7wYr9xNpi6HjBhQDG/mEWB0npmex7eCWfH1yPJ+ChcmchmWEZOMx2BlsHUu+vJ0Ag1O4Eg0ZffN22MtbuWMH6wxsoqCtkxVN/ZtzonlT7qgkEg3y7dS01vtD9eHP1VqKsoXeKX1VvCV2Lvjp8QT976vfxTNdRACy7ZDKugJtP/7aYbgk5HF67Be+WUB/MaXZSVRK6/5V6DmKODiPFkcyukW9R7avh28KNlNQUYz3SPu/8x0ehdxWloXY81D+o59Nli4i1xeAOePAVHcIU7qDIVWy0iXvq9xEkiMlsptpXTaI9gW8nPk+Rq5ivq7Y0KPeMsCbE2+JYV/gJe11FoXs6ZqKskVT7aqjz17Ol6EuS7YnkzriTw3XlRjub5Ehgx6Z1HP5sM4OtAwnU1NM8vBl7tn1tXMNH2xoI9cUzwpqw5+5FxvUYDAaN69GWmcRg60BibTEUuYrxB/14g152fvIpAL37DCTeFkeNv5bUqND7g131u0PPMN5Kwi1hFNQVGu2y/1A1UdYo6vz1RhpSHMl4t+6n1HPQKAvfd+VGvwRCz2hBj89o0/xBP1trvjX6cw6znY2Hv6SwfjcVf3wHp8XBrEGv4Qq48HgD7C7dgXvTbpq2aE+TiZeSmtmaCl8Fl6yZAoTecXz69iK2H95GhDWcb7euxRVw4fK7qfWH3nPbraE6cMBdatwP3J+Hrq94Wxy+otB9f13hJzzvepX1h0PvlFxrvu+vRXZKaXCu/UG/8fwCYIoJvaP8/MA6AHKfnmJse/vC2+nd9zIA6v31xrPHUfZ2jamtrcK96ft3tp9/9QGfffEPIiwRrHr/L3i37Mdz5HnoaJ/jaJv57uB7jOcRjy9A2yXXhPKze5VRd2xmK4n2BCItEUZ/MN2ZRrIjKXSevKHfEuqPXM+fffEPukR3wrO5iNKNm0PP8F4/ngM1nHnp1Qy2DsTnD+AKuDhUfxBTrJNgtYu12z5iW+13uOZ90eB3iW9qtlPsKqFbcneS7aFjfvKX14xrGGDFPTP4ocHWgdjNdi77xxMA5DwylshBoXcHlb4qVq18C4CyLd8a/f4VTzxLl+hOuAIuPj+4nkAwSNil7ThUeYBy72GK60JtSLWvpsH9w5abQUZYEz7b8H07m2CPZ4lvKZGWCKKskQy2DjTS3y25O3u//dpokwD6nBN6xttUFep/d4zvwOZX3sS37DuK1nxOnb/eaFt8+w9jCrNx5WdjjXR4Am7WFX5CyXtrSHOmgCX0PL5r3VrjGDUuH+nOND55cwG1/lrjHU/vPgPZ6yoy3gN/svAVqtwV1PvrWeJbSrGrhDqXjyW+pUbbn2BvREllEa0jWmBy2ih2lRjnodZXa7wjTnYkUemr4rbI0Uab9WSnmZR5DvJV9RbibXGkN2tDm8yuBINB4zny210bQu9g/+U3HfntMJ3Gv98yDVoQERERERERERERERERERGR00KDFkREREREREREREREREREROS0sP5yEBEREREREREREREREREREfk5Rz8XKidGMy2IiIiIiIiIiIiIiIiIiIjIaaGZFkRERERERERERERERERERE6RJlo4OZppQURERERERERERERERERERE4LDVoQERERERERERERERERERGR00KfhxARERERERERERERERERETlFJn0f4qRopgURERERERERERERERERERE5LTTTgoiIiIiIiIiIiIiIiIiIyCnSPAsnRzMtiIiIiIiIiIiIiIiIiIiIyGmhQQsiIiIiIiIiIiIiIiIiIiJyWpzQoIW8vDyysrKMvx49ejBkyBBWrFhxUgffu3cvw4cPp0uXLmRlZfHNN9+cVDyny+rVq7n11lvp378/nTt35qKLLuKFF17A6/X+4r79+/dvUJZH//Lz8/8fUn583njjDbKysigvLz+h/f7xj38wZswYzjrrLLKzs7nsssv4y1/+QjAY/DelVERERERERERERERERETk9DKZTt/fb5n1RHdwOp3MmzcPgNLSUubMmcPo0aN57bXX6Nq16wnFNXPmTPbu3cusWbOIioqiWbNmJ5qc02rRokW4XC5uvvlmUlNT2bRpE3l5eezcuZPp06f/4v7nn38+N9xwQ4N1aWlp/67k/r95+eWXady4MVOmTCEuLo7Vq1dz3333sX//fsaPH3+6kyciIiIiIiIiIiIiIiIiIv8hTnjQgtlsJjs721ju3Lkzubm5vPXWWyc8aKGgoICcnBz69u17osn4jzB16lTi4+ON5R49ehAIBHj66aeZPHlyg23HkpCQ0KAs/1v8+c9/bpD3Xr16UVFRwUsvvcTYsWMxm/VVEhERERERERERERERERH572L6rU95cJqc8q/HycnJxMfHU1xc3GD9xo0bGTZsGNnZ2ZxxxhlMmjSJQ4cOAVBUVERWVhZbtmzh7bffJisri/79+//kMTweD9OmTaN79+7k5ORw//33s2zZMrKysigqKmoQ7sknn6Rfv3506NCBCy+8kGXLljWIa8qUKVxyySWsXbuWQYMGkZ2dzRVXXMHmzZsbhAsGg+Tn53P++efToUMHBgwYwMsvv9wgzLEGJbRt25ZgMEhZWdlxld/P5fl487J69WouvfRSOnXqxNChQykqKqKiooKJEyfStWtXzjnnHN55550G+3788cdcf/319OrVi65du3LllVeycuXKXyVdP1UuNTU11NXVnURpiIiIiIiIiIiIiIiIiIjIf6MTnmnhh2pra6msrCQ9Pd1Yt3HjRq699lpyc3N56qmnqK+v5+mnn2bs2LEsXryYpKQkFi9ezJ133klGRgZjx47Fbrf/5DFmzJjBokWLuPnmm2nbti3vvfceM2bM+FG4iRMnsmHDBsaNG0eLFi1YsWIFkydPJjo6mtzcXCNcWVkZ06ZNY+TIkURFRTFjxgzGjx/P+++/j81mA+Dhhx/m9ddfZ/To0XTu3JkNGzbwxBNP4HA4GDJkyE+mdcOGDdjt9gbl8VOCwSA+n89YNplMWCyWE87Lo48+ypgxY7BarUybNo3bb7+dsLAwcnJyGDx4MEuWLGHy5Ml07tyZxo0bA6GBI/369eOGG27AbDazcuVKRo4cybx58+jRo8dPpvl40/VDX3zxBcnJyURGRv5iuYiIiIiIiIiIiIiIiIiI/NZonoWTc1KDFo7+0F5aWsrjjz9OREQEw4YNM7bPmDGDDh068MwzzxhTYLRu3ZpLLrmEFStWkJubS3Z2Nk6nk/j4+J/9REJFRQULFy5kzJgxjBw5EoC+ffty3XXXUVJSYoRbs2YNH374Ifn5+Zx55pkA9OnTh7KyMvLy8hr8oF5ZWcmrr75Kq1atAAgLC2PYsGFs2rSJnJwc9uzZw6uvvsoDDzzAVVddBUDv3r1xuVzMnj2bq6666pifOCgsLGT+/PlcffXVRERE/GI5LliwgAULFhjLFouFrVu3nlJeSktLeeihh7jpppsYN24cAB07duT9999n+fLlDB8+HIChQ4cacQQCAXr06MGOHTtYsmTJTw5aOJF0/av169fzzjvvcOedd/5imYiIiIiIiIiIiIiIiIiIyP+OEx60UFdXR/v27Y1li8XCs88+S/PmzQGor69nw4YN3HHHHfj9fiNcs2bNSE1N5euvv/7Z/yP/h7Zv347b7WbAgAEN1g8YMIDPPvvMWF61ahWxsbH07NmzwewFvXv3ZurUqfj9fmMWg6SkJONHfoCWLVsCcODAAQBWr14NwHnnnfejuJ5//nlKSkqMGQuOqqmpYcKECaSnp3PrrbceV94uvPBCRowYYSwfHeBxKnlp1qyZEfao6Oho4uPj2b9/v7Fu//79PPXUU6xevZqysjKCwSBAg3P7QyeSrn89zq233kqPHj0aDGwRERERERERERERERERERE54UELTqeTV199lWAwSGFhITNmzODOO+9k2bJlJCUlUVVVhd/vZ/r06UyfPv1H+//r7AjHo6ysDIC4uLgG6xs1atRg+fDhw1RUVPzkj+5lZWWkpKQAoR/x/9XRT0K43W4jrmAwSM+ePY8Z1w8HLXg8HsaNG0dlZSWLFy8mPDz8uPIWHx9Px44df7T+18hLVFRUg/V2u93IXyAQYMyYMVRXV3PzzTeTkZFBWFgYs2bN+tnzcyLpAqiqquKmm24iNjaWvLy8Y85OISIiIiIiIiIiIiIiIiLy38Ck70OclBMetGA2m40f2jt16kRmZiaDBw9m9uzZPPDAA0RFRWEymRg1ahTnnHPOj/b/4eCDX5KYmAiEfjBPTk421h86dKhBuJiYGOLj45k7d+4x44mPjz/uY8bExGAymViwYIExCOBfZWZmGv8OBALcfvvtbNmyhddee43U1NTjPs7PHf/Xysux7N69m61btzJ79uwG58jlcv1q6XK5XIwaNYrq6moWL178o0EUIiIiIiIiIiIiIiIiIiIiJzxo4Yc6duzIxRdfzBtvvMH48eNJTEwkOzubgoKCY84icKJatWqFw+Fg+fLltGnTxli/fPnyBuF69+7NCy+8gM1maxDuZPTq1QuAiooK+vfv/7NhH3jgAT766CPy8/PJyso6peMe9Wvm5ViOzrjwrwMy9u3bx8aNG43PS5xKunw+H7fccgsFBQW89tprDQabiIiIiIiIiIiIiIiIiIj8NzJpqoWTcsqDFgDGjh3LO++8w7x587j99tu54447GD58OLfccgsXX3wx0dHR7N+/n9WrV3P55ZfTo0eP4447Li6OIUOGMGfOHBwOB23btuXdd9+lsLAQwPjkQJ8+fejXrx833ngjN954I1lZWdTX17Njxw52797Nww8/fNzHzMzM5JprruGOO+5gxIgRdO7cGa/XS2FhIWvXruXZZ58FYM6cOSxatIgRI0Zgt9v58ssvjThatmxJZGTkcR/zX/2aeTmW5s2bk5KSwowZMwgEAtTV1TFr1iySkpJ+lXQdHcgxZcoUampqGpRLu3btsNvtp5R+ERERERERERERERERERH57/CrDFpo3rw5F110EQsXLmTUqFF07dqVBQsWkJeXx1133YXX6yUlJYWePXuSkZFxwvFPmjQJn8/H3LlzCQQCnHvuuYwcOZIHH3ywwWcHZs2axdy5c1m4cCH79u0jKiqKVq1acfnll5/wMe+9914yMzNZvHgxs2fPJiIigszMTC644AIjzKpVqwDIz88nPz+/wf7z588/ocEZP/Rr5uWH7HY7eXl5PPjgg0ycOJHU1FTGjBnDmjVr2Lx58ymn62i5PProoz/a/4MPPiA9Pf2U8yAiIiIiIiIiIiIiIiIiIr99JzRoYcKECUyYMOGY25544okGyx07dmTu3Lk/G9/bb799XMe12+3cd9993Hfffca6yZMn07hx4waDFux2O+PHj2f8+PE/GdexfkiPjo5m27ZtDdaZTCaGDh3K0KFDfzKuV1555bjSfywffvjhz24/2bz06NHjR3k51vE6derEX/7ylwbrBg0a1GD58ssv/9EgieNJ1y/lTURERERERERERERERETkv42+DnFyfpWZFv7d1q1bx4YNG2jfvj2BQICPP/6YZcuWMWXKlNOdNBERERERERERERERERERETlJv4lBC+Hh4Xz88cc8//zzuN1uGjduzJQpU7juuutOd9JEREREREREREREREREREQwoakWTsZvYtBChw4dWLRo0elOhoiIiIiIiIiIiIiIiIiIiPyKfhODFkRERERERERERERERERERP6TmTTRwkkxn+4EiIiIiIiIiIiIiIiIiIiIyP8mDVoQERERERERERERERERERGR00KfhxARERERERERERERERERETlF+jzEydFMCyIiIiIiIiIiIiIiIiIiInJaaKYFERERERERERERERERERGRU2RGUy2cDM20ICIiIiIiIiIiIiIiIiIiIqeFBi2IiIiIiIiIiIiIiIiIiIjIaaHPQ4iIiIiIiIiIiIiIiIiIiJwik74OcVI004KIiIiIiIiIiIiIiIiIiIicFpppQURERERERERERERERERE5BRppoWTo5kWRERERERERERERERERERE5LTQoAX5zXD53QA4zQ5W3DPjmGHq/vol3Zv1BWCJbym1vlpuXTe2QRhLpyQAfF8dwDGgFRaTBQBrswSsybHEWKMx2SzERDai1xkXGvuZTSaSM1qwq3InsbZYBlsHEp/VgjhbjBHG7nBy8VuPEiBITlxXfG4/AB1696dzdEf8QR+VdeVG+MyYFqwrXkP39F4s8S0l1hZDZEIiAHGRDqKcVpb4lgIQ7YilyldF39/9IZR+f5BYWywA3dN68tbqQg64SwEYbB2I0+xokO/uzfpiM9mM5W7J3cmKaIUzNRJ8AZb4ltKr6wXf5zcmwvi3s29rmjbKJMWR3CDOIVdnk+xIwhf04zDbG2yzhtlwBVwN1jnMdnz+AHGdUrFmxON21YU2BINEW6MxRzkxOW0k2OOZ8PrVAASqXURaIji7UxoA8bY4rCkxOJMbUemrIqlDWwD8lXWsP7yBPgN+T98/DKN370sBOLirgJ7tBhCbkELWiMtCacuIp0NUaL+MsKYMtg7EZPq+Ocy9ewL+QABbpN0ozxhrNIGqOqw5qUCofrVq1429rqLQuQzLMPaPPL8Ft301kbC0JHJn3EnnngOwXtIKgDVbP8B6RgoAdf56Vn3wVyJapBv7BqrdrMh7zjjGUf6gH3O0A3fAw8T3htPEmU5KeCrl3sNYTBYiLBHYzFaaONMp9x4GoHffy1jiW0rP9ucQZY1isHUg2/dvAaDSW0W4JbzB+Xm693OMu6cfAMmOJHbUFdCqXTfWvPcd8bY4wsxOckffSIw1mjL3QZ6smUN0ZBwx3dtizWiEy+/iq+pQ/Knx6cTYokh3ppHmTGXNe9/xePsb2VW/m2hrtHFsX2kl1sbxPNHhxh/Vl32uYrwBHwBNU1qy332AAAEibJH4g6FrK8ISqqctw5uzq3JnqDq5vAC4Ax5i4hKo89exbvcqmjdtT2xaY/xBPxZT6NraXb/XKGe/P4jT7OQv/W8BIDG5KQCbq7cC0L17OmWegwB0iGoXOl/BIM8v+jJUr5xW3h96vxHm6c4jibXFcsbfb/lR3iIsERS7S6j21eAOeBpsi05Nwx3w4A16OeQ6xOrVy7C1SiYrohWxLTNDgdKi8Af92Mw20pypDLYOpEt0Jyp9VQCYnTaahzcDoNpXQ4w1Gmt6PLmjb6Rd91xe73cLMd3bfn9Qb6g8yzwH+erARqM+V3grAXh38D1GUP/+SrbWfIvz3NYAJMSmEHXXWcb2c199kEOecmJbZhIMfn+OXH//hqDPT7fEbiQ7EnH5XXSO7sjagpU4zA7WH95gHA8gJjqBWFsMYQ4ra7Z+wF8H3IItKwWLycKqj97goCfUliY7kjjzslB7ccBdSoAAuVND53Bd4Ses/e5jAHxBP9HWaHpln8+nf19MsNaLzWQjMyyDPwxoCYDNZMXRO5OJ7w3n0/deb3Beuqf3AiDWFkOxu4TiPRXcun5cKK3WaPa7D9Cz47l8U7P9yLoo2vc4O7Rvk968P/R+49qMt8VR/dm3BKrqGGwdSGZuJunONAK139eTmLgEwhs1Im5EX4LBoBEvQKCyHs+/1JucmC7GuR739CWYj3TvTA47EcmJ5N49gQ13Lgegd5+B+HdVANA1JYfPyz5n3FMXG3k7ej3sqt/N7vq9ADhzWjDYOhBXwMUTHW5ksHUg7Xv1w+cP8P7Q+1l/eINR7wMESLQn8GDcFA64S4mwRNA2sjUrps0i2RG6/x70hs5dj6x+WBKiKXaVABB2ZgY1BeWsP7yBto07U+uvpcJbSbfEbpijHfje2Un//Pv59G+LAbB3SsVhtuMc3hmbyYbV4cDn9htpAciMbg5AnDUWgBUPziSzbTaO7GbEtMwwyg3g03dfJyuildGOlXsPU+evp+qVr5j4/nVGnJW+Kpb4ltK9ezrO3q2o8FaSHt4Yh9lOYnJT/MUVBKrqaBnenNkzVxFmCWNb7XcAdIxuT/f0XphNJuM8JdjjyQhrQrIjiQR7PJ+XfW6cVzMmil37AeiQ3JkfOugpxxVwkRHWhLD0UPk6zHbSnWkk2hPwBnw4zmgGQFR0PABnDhoCQPeMPvRs05+WkS2IdzYKlVN4PH8Y0JJIawQ2k41P/764wfHcAQ9LfEuxtUqmZ5v+xnVR7asx6k6vrhfQJboTPdufg7VtQuhYTXqzb8NGWkwbygF3Kck9snGY7Ay2DqRTVHucFifhljBcARdZKe1Z4ltKXFQCfX/3B2ITUthU9TWAUVcCh6ppOXcEpXe+1yB9R/t0R+va0fMWqPOQEdGUgrpC0p1p9Ox8nhFn64gWbKv9jmR7EuGWMMItYUZ8YWdl4AuG7il9f/cHLjqnFblTxpMcnkwTZzo9O55L92Z96RzdkdR2SQSq6ox9j16zSfZQGdi7ZoSuhel5ACzfuI8BL01liW8p4bGxDfLhDXqh3kvj5vG4/C6yU7rSJbYzZ8RkE2GJMOLOietKta+GRrZGJNsT6d09dC07/9ABgK9ueAZLUqifanJaWf3QswCEW8Jo1Kol9k5NWXH3DKy903EFXJjbNGLVyrdo8/RN2Ew2+l7+B4JeP2eef6XRz0t2JNG5STd6tDqbrIhWRpq79jovdOzerfAF/VibNMJishj5hVCd9ga9tI1szRnJOcTYoo1tifYEHGY7af17AHDJ0sewNgvVy54dzyXdmcb7Q++ne1pPoqyRoTI6cu9yBVxctv5mXAGX0T+wNk0gQCB0fTrTSI/PMPq5Z3dKY3vtTpb4lpIZ0wKAw3O+AJslVA5OG3WHvj+XroCLnLTuAAx4aSp1/nrjOPgCnBGTDYT6akt8S8kIa2qUVYw12iiX7l1CfVlTmIMeLXNpltneyHu1r4YeLXPJimjFintm0C0hBwjdX1wBF3X+eiwmC21i2xB9JE6TzUJSagYOs914Tooa0YWg20dkmM24T9T566ms/f7fUdbIBv32xs40oqyRnHnJVaSEhfqoqY5kYqzRdIpqjzfoDdVTSzix1liiouNpkhBOZliG0X5GWSMJt4QRZYnC5Gg4mWPjVm1pnBxJufcw9f56BlsH0i6yDQlX9CLBHmqX1nz7IU2c6RS79hvpXuJbSqWvijRnKvd+9xJtUzrSxJnO+vIv6NmmPxlhTb6vP0f6bADuTbsJEqDYVcKTNXOwn92cWFss6c40o2/UKNqJGTMH3KXsdx/gmZveJMoaCUC31B50S+xGrC0GZ6NwmjjTSXemGW3D+QunGce6+uwWuAMeqn01dIhqR4w1GqfFyWDrQCNM1Stf0cSZTpozlTYDzmFHXQH+jQcI1rqxmW1GXgHi7XGs2bKcPmcNYnvtTqwDW/FkzZxQupK7G+etU1So7kRHxxv3kl5dL+DzA+uo9deScEUv6gL1OIZ3otpXQ9DlxRYXFSqfgMfomx3tS7UY1x1v0EuKI5mm0RnE2+Lo2fFcAEat/zM3rn0Wh9nOrvrdAExYcjUr8p4jzhrLa8u/Iyemi1EHj/YhG6WFzk8gGMTWNokKbyVpbdsz8f3rSHYkkeQIPfPmxHU1yqqgrhDAeL67Y2s+cbZYvEEvg60DCRyqDuU/uQt1/nrG3d0Pp8VBuCWMJs50umf0IdwSRo/mZ1H3xQ4AmrXuxLCL29Kz47nkxHUl3hZHiiOZJ2vmEGONptZfi9PiJCf+DJyW75+fzzz/SqNMsq6/lChrJPYhHYnLCaXNHGanW0IO7oAHW9NEEuzxpDhC9waAS//2OAB9/zDMKMujz+ofvb6Z9lFt6NmmPwCr3v8LTrOTOn89t301kcywDDz/+M5IS5Q1iq/2f8mOugKahzfjmnNCbW+8LY7MsAzSnY2xmWy0jWlDnC3GaHcA2jTNpntGHyB0XyrzHGSJbymOAZlGvTl6Dro36U1g1V5e73cLEGovGjvTjHp39D2L9/0C7Gc3xx/00y25Ox2i2pHsSKLGV0eL5p3odPb5OM1OEu0JxFpjaeJMJ7t1b6KskWSENQmVWUwkKY5klviWsq7oM+JtcQQIGOn27jzAYOtA1mxZbvT7ttV+1+D9TJnnIDG2aFIcyZhjQ3W6iTPduEcm2hMo37TfCO85UA7RoXNc7ath9bq/0yW6EylhKQR9fhKP3K83V28l6PEbfY6j5+3o9pbhzY3nkUOVLsyYiYiK4fBXJdT6a78v+6dvwl9SSYI9PvTuIKIFBz3lxP7L+yOXP9T3b9MkFqfZGcp70EuCPZ5idwn95t5n9G1K9law8KybAfj8wDpahjcn3BKGP+inTaN2tEhojSvgMtqTbondqFm/D2/AR7GrhChrJDX+Wrqn9cTl8bOu8BNqfaF7XYQlosH7jJSwFA59HSq7/e4DAHw86iHwBegc3ZGmYY359B9LWPXRGwC0i2wDQK2vjkBxFd6glxhrNOa4MF7vdwv+oJ9eXS9gR10BnhW7GWwdSGHdbjLCmvL6JwVkhDWhzl9PmecgB9ylbK8NPdev3fYR22q/o66iAn/QT4AAbSNbM+ClqbgCLhzDOxlpbpHQmsPeSqPfFt8q9AxwtL1cV7yGzp1zcQVcxDVv9n09ch8kwhpOnb+ewJH3CEf1OuNCWke0oHnbLjjMdur99XSJ/v6Y8bY4KryVRh0NekLvLg56yln73cdYz84gI6wJAQJ8U7OdYncJJsws8S2lTWQWTrMTs8lEsLzeaI//0v8WnGYnXaI70SW6E7kP3AqE+vdmk4l23XON+1VGWBNiraH6lGCPp5GtEVHWSMyYaRrWmCf3LwQg9+bRRLdvTt+rr2VfzT7ictpibR5qg+sDdbw/9H4AoixRrF73d0rdZTh+1540ZypZKe1JS2lhvLNoktYKb9CLyWahRXhzlviWYsZs3F8jLBHY26cTdPtIcSQb7UZW5PfvXiMsESTaExi89kHCLWE0dqY1KPdm119IhbeSnm36kxXRisywDGJtMVT6qggQwGKy0D65I19Vb6Fu+gdEWSPplhrqP35R+SVxthgSruhltC/bar8js28fWke0MOrK0ft0ujONZtdfSMu5I4w2KMoaadwn/eU1DHhpKk6zk9YRLQgQCL1DaB96/g5U1dMivhVpjlTjGS7RnsAS31JSHMnU+esbXFtmp40D7tIGzxtba77FfkYTMsMyjHK0npGC0/x9f2JHXQGfffke++/8p7FfujON1CPvaAPBIF2TzqBZWAabqr6mzl/Pp39bTI2vjodbX0+iPQFn71as2bKcFdPzWLP1A5qFZdCz7ffvePuc83saO9Oo8FbSrnuu0Qe1mWzkxHQhEAwCcOZlVxvv8xw9QmXqDniwtw/d/3q26c9g60CjzbRlJBrHGD6wXYM+EsCZl1wFwDMj38LaLhT26LlK7JRihMu9dQxpD/RjsHUgKUf6qf/q0/deJ9wWjq1FspHOM9J70L1Jb/xBP2ddOxxrRjz23qHzUeev56lec4w286zrrzfuh/UeP1suzA+tv3a4UR+iouPxB/0UuYppGxl6H9akfWfK3Aexma00TQqlO/JI+O5NehM1OIfy8gPsqCsAIBgIgslEwfsrWOJbSiAIcbY4wixhrMh7DnNiJJ2i2tPYmUbnxUPoEt3JKLMzL72aJs50kv58OTvqChhsHciZl1xlXMMAF/5luvFvpznU313iW0qyI5H9E5aF6sumA7zz+7uMcEf7KTvqCljofZMlvqV0S8ihyFUMhJ6xrSYLdQu/ILFJJpGWCNLCv39HH2+LM+Ia9+C5+IN+WoY3N9b5jjw3VfqqjHcpR8sj/LJONOmYbbRJAP7iCgDjuv784HrKvYdZ9cFfaTbiQqKskQx48Y9HzmMdn7y5gMXtZ5B+pC2JtkbTs/N5pF7Qk29qtrPi0WcASHN8X5+KN5aQntWBM8+/kpyYLoRZwljiW8oFr15BhCXCSF/ubWOJTUihTWQWEOrnHtocui8ebfsPuEtJCU9ld/1eTHYrOTFdjPtilDWS5uGhPleZ+yCJzkSerJlj1PHbvppIoj2BbsndqfXX8u3OL7BmNAq9+7aGrrO2rbuR2b6L0YbKb4vJZDptf79lGrQgIiIiIiIiIiIiIiIiIiIip4UGLYiIiIiIiIiIiIiIiIiIiMhpYf3lICIiIiIiIiIiIiIiIiIiIvJzftsfaTh9NNOCiIiIiIiIiIiIiIiIiIiInBaaaUFEREREREREREREREREROQUmUyaa+FkaKYFEREREREREREREREREREROS00aEFEREREREREREREREREREROC30eQkRERERERERERERERERE5BTp6xAnRzMtiIiIiIiIiIiIiIiIiIiIyGmhmRZEREREREREREREREREREROkWZaODmaaUFEREREREREREREREREREROC820ICIiIiIiIiIiIiIiIiIicopMaKqFk3FCMy3k5eWRlZVl/PXo0YMhQ4awYsWKkzr43r17GT58OF26dCErK4tvvvnmpOI5XVavXs2tt95K//796dy5MxdddBEvvPACXq/3F/ft379/g7I8+pefn///kPLj88Ybb5CVlUV5efkJ7bdixQqGDh1Kz5496dChAwMGDGD69OlUV1f/m1IqIiIiIiIiIiIiIiIiIiK/RSc804LT6WTevHkAlJaWMmfOHEaPHs1rr71G165dTyiumTNnsnfvXmbNmkVUVBTNmjU70eScVosWLcLlcnHzzTeTmprKpk2byMvLY+fOnUyfPv0X9z///PO54YYbGqxLS0v7dyX3/01FRQWdOnXi2muvJTY2lu+++468vDy+++47XnzxxdOdPBERERERERERERERERER+Q9xwoMWzGYz2dnZxnLnzp3Jzc3lrbfeOuFBCwUFBeTk5NC3b98TTcZ/hKlTpxIfH28s9+jRg0AgwNNPP83kyZMbbDuWhISEBmX53+Kyyy5rsNyjRw/sdjv33XcfBw4cIDk5+TSlTERERERERERERERERETk38Okr0OclBP6PMSxJCcnEx8fT3FxcYP1GzduZNiwYWRnZ3PGGWcwadIkDh06BEBRURFZWVls2bKFt99+m6ysLPr37/+Tx/B4PEybNo3u3buTk5PD/fffz7Jly8jKyqKoqKhBuCeffJJ+/frRoUMHLrzwQpYtW9YgrilTpnDJJZewdu1aBg0aRHZ2NldccQWbN29uEC4YDJKfn8/5559vfOLg5ZdfbhDmWIMS2rZtSzAYpKys7LjK7+fyfLx5Wb16NZdeeimdOnVi6NChFBUVUVFRwcSJE+natSvnnHMO77zzToN9P/74Y66//np69epF165dufLKK1m5cuWvkq5jiY2NBTiuT2eIiIiIiIiIiIiIiIiIiMj/hhOeaeGHamtrqaysJD093Vi3ceNGrr32WnJzc3nqqaeor6/n6aefZuzYsSxevJikpCQWL17MnXfeSUZGBmPHjsVut//kMWbMmMGiRYu4+eabadu2Le+99x4zZsz4UbiJEyeyYcMGxo0bR4sWLVixYgWTJ08mOjqa3NxcI1xZWRnTpk1j5MiRREVFMWPGDMaPH8/777+PzWYD4OGHH+b1119n9OjRdO7cmQ0bNvDEE0/gcDgYMmTIT6Z1w4YN2O32BuXxU4LBID6fz1g2mUxYLJYTzsujjz7KmDFjsFqtTJs2jdtvv52wsDBycnIYPHgwS5YsYfLkyXTu3JnGjRsDoYEj/fr144YbbsBsNrNy5UpGjhzJvHnz6NGjx0+m+XjTBeD3+/H5fOzYsYPZs2fTv3//4yoXEREREREREREREREREZHfGpOmWjgpJzVo4egP7aWlpTz++ONEREQwbNgwY/uMGTPo0KEDzzzzjHFiWrduzSWXXMKKFSvIzc0lOzsbp9NJfHz8z34ioaKigoULFzJmzBhGjhwJQN++fbnuuusoKSkxwq1Zs4b/a+/Ow6soEr2Pf/vs2UNYQiBIwhaRsIjsWwBxxcsg46CMCgoIKjCCqAPzihdcrl4GRiGiGMVRRFnmDgoo4g4qCAhhR1CEsC9hy56c9f2jk8Yji4DORIffhyfPc053dXV1VXV1dZ+i+tNPP2XGjBl06tQJgI4dO5Kbm0tmZmbYD+p5eXnMmjWLhg0bAhAREUH//v3ZsGEDrVq1Ys+ePcyaNYsJEyZw6623AtChQwdKS0uZNm0at956Kzbb6ZNU5OTkMHPmTG677TaioqJ+Mh/feust3nrrLeu73W5n69atP+tYjhw5whNPPME999zDsGHDAGjatCkfffQRH3/8MQMGDADgjjvusOIIBoO0bduWHTt2MG/evLMOWriQdAF069aNw4cPA2aZnWmgiYiIiIiIiIiIiIiIiIiIXLoueNBCcXExTZo0sb7b7XZeeOEF6tWrB0BJSQnZ2dk88sgjBAIBK1xKSgpJSUls2rTptB+3z+Xbb7+lrKyMq6++Omz51VdfzVdffWV9X758OfHx8bRr1y5s9oIOHTowfvx4AoGANYtBjRo1rB/5ARo0aABg/cC+YsUKAK699trT4nr55Zc5ePCgNWNBhcLCQkaMGEFycjKjRo06r2O74YYbGDRokPW9YoDHzzmWlJQUK2yF2NhYEhISOHTokLXs0KFDPPvss6xYsYLc3FxCoRBAWNn+2IWkCyArK4uSkhJ27NjBiy++yL333svf//73sDAiIiIiIiIiIiIiIiIiInLpuuBBCx6Ph1mzZhEKhcjJyWHy5Mn8+c9/ZtGiRdSoUYP8/HwCgQBPP/00Tz/99Gnb/3B2hPORm5sLQJUqVcKWV61aNez7iRMnOHny5Fl/dM/NzaVmzZqA+SP+D1W8EqKsrMyKKxQK0a5duzPG9eNBC16vl2HDhpGXl8fcuXOJjIw8r2NLSEigadOmpy3/JY4lJiYmbLnL5bKOLxgMct9991FQUMCf/vQn6tatS0REBFOnTj1n+VxIugAuv/xyAK688kqaNm3K7373Oz766COuv/76s+5DREREREREREREREREROS3SG+HuDgXPGjBZrNZP7Q3a9aM1NRU+vbty7Rp05gwYQIxMTEYhsHQoUPp0aPHadv/ePDBT6levTpg/mCemJhoLT927FhYuLi4OBISEsjKyjpjPAkJCee9z7i4OAzD4K233rIGAfxQamqq9TkYDPLQQw+xZcsW3nzzTZKSks57P+fa/y91LGeye/dutm7dyrRp08LKqLS09F+WrrS0NJxOJ3v27Lm4RIuIiIiIiIiIiIiIiIiIyH+cCx608GNNmzalZ8+ezJ8/n+HDh1O9enVatGjBzp07zziLwIVq2LAhbrebjz/+2Pqf+wAff/xxWLgOHTrwyiuv4HQ6w8JdjPbt2wNw8uRJunfvfs6wEyZM4LPPPmPGjBmkpaX9rP1W+CWP5UwqZlz44YCM/fv3s27dOuv1Er90ujZs2IDP5yM5Ofmi0iwiIiIiIiIiIiIiIiIi8mtmaKqFi/KzBy0A3H///SxevJjXX3+dhx56iEceeYQBAwYwcuRIevbsSWxsLIcOHWLFihX06dOHtm3bnnfcVapUoV+/fkyfPh23203jxo1ZsmQJOTk5gDnzA0DHjh3p1q0bgwcPZvDgwaSlpVFSUsKOHTvYvXs3Tz311HnvMzU1ldtvv51HHnmEQYMG0bx5c3w+Hzk5OaxatYoXXngBgOnTpzNnzhwGDRqEy+Vi/fr1VhwNGjQgOjr6vPf5Q7/ksZxJvXr1qFmzJpMnTyYYDFJcXMzUqVOpUaPGL5Ku4cOHk56eTlpaGh6Ph23btlmDOs40+4aIiIiIiIiIiIiIiIiIiFyafpFBC/Xq1ePGG29k9uzZDB06lJYtW/LWW2+RmZnJ2LFj8fl81KxZk3bt2lG3bt0Ljn/06NH4/X6ysrIIBoNcc801DBkyhMcff5yYmBgr3NSpU8nKymL27Nns37+fmJgYGjZsSJ8+fS54n48++iipqanMnTuXadOmERUVRWpqKtdff70VZvny5QDMmDGDGTNmhG0/c+bMCxqc8WO/5LH8mMvlIjMzk8cff5wHHniApKQk7rvvPlauXMnmzZt/drqaNWvG4sWLycrKIhQKUbt2bf7whz9YgztERERERERERERERERERP7TaJ6Fi3NBgxZGjBjBiBEjzrhu0qRJYd+bNm1KVlbWOeNbsGDBee3X5XIxbtw4xo0bZy17+OGHqV27dtigBZfLxfDhwxk+fPhZ43rmmWdOWxYbG8v27dvDlhmGwR133MEdd9xx1rjeeOON80r/mXz66afnXH+xx9K2bdvTjuVM+2vWrBn/93//F7asd+/eYd/79Olz2iCJ80nXkCFDGDJkyFnXi4iIiIiIiIiIiIiIiIiIwC8008K/2urVq8nOzqZJkyYEg0GWLl3KokWLGDNmTGUnTURERERERERERERERERERC7Sb2LQQmRkJEuXLuXll1+mrKyM2rVrM2bMGO66667KTpqIiIiIiIiIiIiIiIiIiAiG3g9xUX4TgxbS09OZM2dOZSdDREREREREREREREREREREfkG/iUELIiIiIiIiIiIiIiIiIiIiv2aGplq4KLbKToCIiIiIiIiIiIiIiIiIiIhcmjRoQURERERERERERERERERERCqFXg8hIiIiIiIiIiIiIiIiIiLyM+ntEBdHMy2IiIiIiIiIiIiIiIiIiIhIpdBMCyIiIiIiIiIiIiIiIiIiIj+TgaZauBgatCAiIiIiIiIiIiIiIiIiInKJ+v7773nyySdZt24dUVFR/O53v2PkyJG4XK6zbnPkyBFee+01li9fzp49e4iJiaF169Y8+OCD1K5d+4L2r0ELIiIiIiIiIiIiIiIiIiIiP5PxG5xoIS8vjwEDBpCSkkJmZiaHDx/mmWeeobS0lMcee+ys223ZsoWPPvqI3//+9zRv3pwTJ07w4osv8oc//IF3332XhISE806DBi2IiIiIiIiIiIiIiIiIiIhcgubMmUNRURHPP/888fHxAAQCASZMmMDQoUNJTEw843ZXXXUV77//Pg7HqSEHLVu2pGvXrrzzzjsMHDjwvNNg+1lHICIiIiIiIiIiIiIiIiIiIr9Jn3/+Oe3bt7cGLADccMMNBINBli9fftbtYmNjwwYsANSsWZOEhASOHDlyQWnQoAUREREREREREREREREREZGfyTCMSvu7WDt37qRevXphy2JjY6levTo7d+68oLh27drFsWPHqF+//gVtp9dDiIiIiIiIiIiIiIiIiIiI/IZdffXV51z/ySefnHF5fn4+sbGxpy2Pi4sjLy/vvPcfCoV48sknqVGjBj179jzv7UAzLchv0M7iHO74MvOM6xyXVWPjnq+t7wfLDlufG0c3AmDZX6cx7clP2TBtNil3XYnb5gJg+cf/ZMXq9/CFfGw8sI6NuevZuP5za/soexR7cr7hqPc42wu/Y55/IauyP2Rf6QErzNe5X+Mv9nGg9CCeLo1YOvAJM+7P3yGibk2Oeo/jMJxW+L35e2hbrwur933FB2v30SjxCrbv2wDAor99yR0RNzMubjR9Hb3YcGIjR73HOfKheXyT6zzCUe8xADYf3kDvDinUjagDwDz/wtPy5t7NI7Ebduv7d8e3E1e9Jhvufp5lzzzPy7PXc/m0/wKgwF/I+m++PHVci99mw6Fs0v737vA4q/yB3LKjuG0ujB81J1/c/RSF/uKwZR6bh6FRd/DOdQ+y7v132VK4DYCvspdQEihhxcp3WbnpI74t+h6Avo5eRHRvzN7SffR19AIgxhHNipXvsnXXGlIj6rJt3Qo27TrO/t3b+ePnU1m3dDGb/rGAkZ/fA8CO4p1s+24Na3Z/RfBQIQDr3n+XNXnrzLwr2Mo8/0I25W+x0ln88krmZDzAx3eN50DpQboMHEhxoITVu5eTM22RFW7V+o+ItEcAcNh7apqbwjUH6Ovoxartn9G+Zxorli9k2AMdARiw4nlW/e1VANrUakebWu34av0H1rbLP/4n17zx+GnlF2WP4vOZrxHvjCN7x1Hq9ujImuNrOVyWy+Cvn6dJUjMK/IUc8R4hEAoQJIh3yz4AnFfUZGvBNub5FzJi6xQA0uOuYHPB1rB9rFj9npXP9Vu1o3VSW1at/4hlI5+hQeLlVItNpGjeOrq++9+0btCZSZf9D3tO5rD8k3+yasnb7CrZTU13In0dvVh78Gv8oQAHyw6T58tn2chn6DJwILO9CygJlFj73nxyCytWLGKef6F1bry2YAvr8jdSFvSyq2Q3ABv2fk3Hbn1oEFmPNSeySXTXAMy6ChBpj+Co97hZLl8vAeCquBas3vcV3xR+S8aY4azasYwN36+kdbVWFPgLGBc32jr/AdY+9TmNoupb58/qnC8ASItqCEBeoZdGUebIwCE7/xuAQCjAR3c8BsCJxd8yevPLVtqePzqXo95j/KFzPeIc4Rf7k748ouxR2A37aeWw6rulRNmjSI+5gl0lu0mNqMuXH/yDEEHWbPgUgGXD/we3zUWeL5/iQDHz/AuJ/d//ItFdgzV561hzYDXJfbsB0Lp6a7q++99s/uJj2j3Qnm2rv2CefyHLP/mntc87F9wOQL4/n3aj77HatXhnHAAvnviHFTZ711d0aNOTZS++DMDXB1dZeQDw+56NqRabyFfrP+AO980c950AwHN7C9acyOa7k9+yJm8djaqksbdkH3bDzuGyI3QZPJB6kSlWPOsPZdMo8QqeazycASueJ+PF/8fXH7yDw7CTce9gSoOlTEp5mssSUrnt1T5WPWid2IZhj3YHoH3L6xmx7iUAigJFHPMeJ2pUBzIeH8W2Dz4kzhmDPxSw6v3ukr188dZMADp26R1WLpSPUnXb3ETbo0itX9VatatkN82bZ+Dff5yMaf8PgG+LvmfTKrO8thzYwOjNL3NVXAsAthd9R/y46yk4cZR5/oW81n4Yl780FE9GQyvO1fu+YnXOF6ya+hq7SnbTvsV1TEp5GoBNa5aS6DLr2a7hr1vnQaK7BtOe/JQ6EbUB2Lx3DZt2rab45ZV8+YFZhnvXZmOrEWWVXUV9BajiiLc+1/EkkxZtpufbL5Yxz7+QAn8h8/wLmedfyFefL2RCwsM8e3g2bdO6Wdt1GjWU7LwNVL2zE21qtSPXe5QdxTvJeGQ4MfZo+jp6caD0IAD+QydYueVjqrkSABh4S1O+e/QN/vj5VBy1E+hyxwDinXGM2vcon898jbyVW4msFkX/5c8DsPat/8Nj81AttQq7SnaTfTTbuu7ayq9JXx9dY5URwJ/Wv0T2xs9Y/tl863yqKJcu/e/CaXNa19JmMU1oHN2IL9+ZDcCUa14DsNqBvEIvX74/j84vjmXNiWz2lR5g8941PLjxATAMdpXsJrlNMjbDIGPIYAA25G9i55Ht7C89ZJVT3YjLKPAXMnLH36hftxmtk9qSc7iAAn8hB8sO4w16zeM9eKp/U8Eb9NIspglbC7dxeNcOM19DAbYXfccVd/XmuO8EX747l8z+/8eWw5vMPPi/fmb92JdN/xX3kn1iPTsLdlr51dfRi28Kt1PVlWC1h00H/T5sv19+8A/Wbv+CvBNHAcLa0sChk8T+z00c2bWDollmmrcc2MBfC6YxbGQnPDYPyz+bz+6SvczzL2RjwRY25G9iUu7rtHzqPtbsWwXAptyNjPjHbazevZwEZxUAWie1pa+jF+sOrqXg6WXUmRp+41PR1l4Wc1nY8m/2rWNH4fe0qduRfaUHuPof/ajlSQLg0dxJVHdVY3vRd5QFvfiCfmu71PpVrb7MiH/cxvys1Qx67Go2ndxEUkIywYJSdh34hpvXP0SfjqkUlOcHQKfr/sCklKfZU7IfAHtyDIfLculyl9mXSq4WxdA7WwKweu+KsPRmjLqPZS++zN/bDyPPn8/6Q9msOZGNPxTg8nZdrHbG3fQy7lzzv+wt3cf2ou+IHNYGgML/NfuvN6+YwKrvlppl9v48q8/isrlYveFjVn76Dl2nP8rXT2UR44jmvoGt6fzH/iy77ymquhLYtOg9vnxnNlVHtaP9i38GwGk4WLtnJWt2fIHT5rTaT+cfrgAgZWwnDpUdJnv9p7SsemVYnzR9yWAi7REM/m482UfWWm0BQHGgBI/NQ6+XzPgKNh/Gt8PsW+V8u5EDpYcYvfllfIXFdF80ni73DLKuXYFQgMxGoynwFzJk/bMArFi+kE6jhtK6emu2F33HuoNrcd1o3gv0dfRinn8h2/ed5Otcs462/d8erFrxHid9eaw5sJqTo9+1jq3IX8zqAysBGHpnS4oCRTSPbQrAqvfms7tkDwADV04DsK7rMfZo617ky/fnMb7eAADW7V7JPdkjWLvd7GdUd1WjNFjKPdkj2Fu6j9eK5nOw0OxLNqp6OZ3/cAcxjmgK/IWsPZrNofI4v/5qCat2mmV9ZbMMAPbfPYuvc79mSNwt1vW3RZPOLOkwrbz8nKQ360SDmo2tvN9bug9v0Ev2+wvpt/UhAL4p/JYYR7TVdgJszN9Crvcoqw+spEOTmhzxHuWKgb0ByPcVkOs9arbF335J89h0a7uVmz7i6xtepVlME4IEmedfyN7SfXz+2t/xhwIAZNw/hJP+k3iDXtyRUda2jaLqc8x7jC/mb2X1vq/I9R5l0KoXCJwotNoFONVnA1hzfC37Sg9YfZjsqTM56j3GgdJD7Cg227q/Nryfzo/cz1VxLWiT3J7omxrRINL83yS2KA9HCg8RCoX4oN+jJFW/jJ3FOXhsHgBKd57gh5I9tYi0RxAMBfHYPWzI38Q8/0Kr/nz5zmwCBDjmPcZXS/5Jg8h62Ltcxva9G8jz5YfFsyF/Exn3Dmbzik9pXb01wa9PnSM5J3bSbsxQAOue7uuDq+j8yP00j23Khg3L6Hzbndiw8flrf6fIX8TKIX8lwVmFPfm7Wb3bnMoz2hFpXVcq/L39MACOeY+RfTSbGg0b8c03q5j21Gfkniwl90QJdsNOgrOKVSeueeNxdpXsZsH1o7FXjSE10mx3q5Zf07fvXg/Acd8JPp/5GvtKD/BVttlHP+k7yZGyXACSZt4GmOflQ5tfAWDbOrNNXND6GbYVfsfO4hzm+Rey9mg2na77A+sPZdPu8u70dfQivU4rqjqrsr3oO6IfuxqPzYOzWW0rnSs3fQRA5Mj2fJO/nQNlB4m2R1n5WM2VwIb8TUSN7U7j5CutPPHvPW72hf7yR4rmrWNzwTeUvrCS5UvfBmDPxnV0/mwoh8oOk/PtRlKrNsRh2HHazP8XlL8sB4CS9zYRLCgF4MrYZgDUbJvM2rz1uNqYeXbf2ulUd1XDbtjNflLZQYYvH2qlZWfxLtqOuYf2rW8k2h7F/OW7AKjlSaJ6tdpsLthKgb+QNcfXsrFgCx67h3aXm33hVTs/p8rT1wPQruk1Vh/m0zsnAOY1e8NJs39w94aR3P36761+VoKzCke8R4gtv7a629QFwNkyieypM/n90kkcKzhCcaCYGHs0e0v3sXLbpyz/+J9cFlGbAn8hx30nyPfns3Lbp6zL30iEPYKMx0exeu8KGnTtAsBDm1+hNFhq9Uk35G9iTd465vkXkvG/D9Ol/P23HTr2Yt26z6x8ibJHcaD0IKnpLVm51Xzour3oOzIeewCAlKr1qd26dlg/v1abZPNYbC4aRdWnKFBEv60PseZENpdFmOvaNenB8s/mW+VVce5Xd1Uz8ywUoJY7iYx7B9MpPYmdxTl8d3Qbw0Z1psvgU+/qXXbfU4TK/ATK27mckt20v+oG4hyx3LhqNAB5frMNeGdFDr6QDzD7sPGOeK5qcy2tOtblm8JvaVS7GSVbc2lbrwudet7KGyXmvXfdf9xF24ZdWXt4DdmH1hDjiLb2f9+uMQx7/BqO+04Q74wj359PSmoTHtg5hmeb3EvG83+hXWfz+Y/DsIc9K+q39SGGjTCfX9R0m+8tHrvtVVa9N5/vinbwTeG3ZvncO9jKW4B2nf+Luz66m2quBDx2D7jtzPMvNPvWwZDV3nYZOBBfyMe6vI38oXM9DpQeoporgXaXd8du2K2+Q9sGGUw++BabC7ZyzHsct83FN4XfsnTgEzSIrMfKIX+10px9aA17S/dZ/bbVGz4GsJ45vXh8HquyPyQ1oq7VLgC0btCZAn8hu0v2hl1LALLXfcKjuZP4av0HNKvanFruJOu+q6K+JXtqWemtuO/w2DxcFdeCZY/+jVzvUQr8hUTaI7iqzbVWPdqQv4n0mMa0+98HWPaXybSp1Q4wn+W1n/4wRYEi3LWqMeTPGfR19LLyeNvqL8gvrzf7Sg9woMy8Tlx+dQ/2lu7DF/Jx3HeCbwq/ZcH/LAOgz6Nd+XrVB9iqR1I7ujbLl77N2k/fA6As6GX0ZvO+fm/pPl4vmk/DqPosezqT74p2sOHAWlbnfGHdpx84sJP0mCvYeGAd24u+A8x+ZbQ9ika1m9EkqRlffTifjXu+JkSIHh/cbR3vgdKDbMrbTK73KFExcWT/v09p1rA9R8qfpVWcq8Om3kSr5LakZvWm5t3d8IcCdF70KKkRdakXmYLDsPPNkc30/uBvPHzoMdblb+Trg+b9w98L5xMXmcDnr/0dgBeOzzPL/OO3+b44x6orFWV23bJHGTb1JgqeXkazmCbmMZYesvrMuQd2M/TOlkTbo4iLrkrrpLY0jm5kXc/cA67EsNs44j1Cqyot6evoRYggAA26diHeGUeeP5/2V90AwJoDq7kythkv5r9pHW/bBhlsm/8+6/I3Wv2UVX97leYpbax0tr/qBl4t+CeBg2YfpHlsU/aVHiCxldlOJXtq8fXh1azJW0fGw8Oo5Umy+ltjtr1KVGJ1vnx/Hh3a9KRb1jjeKlvA5oJvrDTc8WUmvq372V70He1bXs+21V/gsXtIj7kCX8hH+pLBVj+2xoi2HC4zy2zFe+YzhqZXdOCrD+cDkJrVm3n+heR6zfuilSsXW+fMW5/uYJ5/odVH6zJwIMHj5jk7PKs3nww0r00Vz4QPv7jG2nbYX2+gb5d6zPMv5FDZYfL8+fR19LKOoWOX3mw4uYnvNph99j/984+s3ruCAetHUs2VQLDAy7r332XZC1mA+Wz5q69Ppa3si50cKDHPpyFxtxA1orOZlnlLrH7TlsObOO47QasqLfmm8FsARq26j9YNOnO4LJctB8zn+TvL69qA9SPZ/sa77C3dx8gN5n7XHF/LstH/S8O7bwJgSvKT5HqPsrVwG9e88ThfvjeXLYXb2F2ylx5X1iYiva5VD3730n9x3HeCiHgP7VvfSJeBA9nx0VLrHAbwFZ3q48U746xnGzuLc6j7svncrPSTbdZ9S3rMFUSObA/Af737V16evd5cvuhuJh7PYmbx26RG1KXAX8jDhx5j1fbP2Fd6gOzj66x4K+6rwTyPJxdMpyBwqq30l1/fIu0RpEaYfYn2rW8E4I8Tr+OrrxdbbRJgPk8BDLv5TKfTTbfSqkpL5vkXsuz5LA6VHWZo/6sA8/rz/NG5eDLSrHuD74q+Z92mpXwx/y0SnFWs/NtUsMVK47IHnubBtcPx7z3OI8cmWM+kEmLcOAy79Txp2MTrWbP7Kzbkm32lw94jLBv5DHDqt5dkTy225m3l4e0vsXb1h0T9uTs9vhwFmO30zmKz39a6QWeyT6xn0mX/Q7WW6VZadhbncDBvH80va4s36GXHF19wVVwL63qzcusnuG5pYtU5+W0xjMr7q2yZmZmsXLmSiRMnEhkZeUHbaqYFERERERERERERERERERGR37CzzaTwU2JjYykoKDhteV5eHnFxcecVx7x585g2bRpPPfUU7du3v+A0aKYFERERERERERERERERERGRS1C9evXYuXNn2LKCggJyc3OpV6/eT27/0UcfMX78eP70pz9xyy23XFQaNGhBRERERERERERERERERETkZ/otvh6iS5curFixgvz8U68yXLJkCTabjY4dO55z21WrVvHggw/yhz/8gWHDhl10GjRoQURERERERERERERERERE5BJ02223ERUVxbBhw/jyyy/55z//ycSJE7nttttITEy0wg0YMIBrrrnG+v79998zbNgwUlJS+N3vfsf69eutvz179lxQGhy/2NGIiIiIiIiIiIiIiIiIiIhcogx+xpQHlSQuLo7XX3+dJ554gmHDhhEVFcUtt9zCqFGjwsIFg0ECgYD1fcOGDRQUFFBQUEC/fv3Cwt58880888wz550GDVoQERERERERERERERERERG5RNWvX5/XXnvtnGHeeOONsO99+vShT58+v8j+9XoIERERERERERERERERERERqRSaaUFERERERERERERERERERORnMn57b4f4VdBMCyIiIiIiIiIiIiIiIiIiIlIpNNOCiIiIiIiIiIiIiIiIiIjIz2RoqoWLopkWREREREREREREREREREREpFJopgUREREREREREREREREREZGfSRMtXJxKm2khMzOTtLQ0669t27b069ePZcuWXVR8e/fuZcCAAVx55ZWkpaXxzTff/MIp/tdasWIFo0aNonv37jRv3pwbb7yRV155BZ/P95Pbdu/enbS0NCZNmnTaupycHCuPV61adUFpyszM5Morr7ygbQA2bdrE2LFjueGGG7j88ssZOnToBcchIiIiIiIiIiIiIiIiIiL/+Sp1pgWPx8Prr78OwJEjR5g+fTr33nsvb775Ji1btryguKZMmcLevXuZOnUqMTExpKSk/AtS/K8zZ84cSktL+dOf/kRSUhIbNmwgMzOT77//nqeffvont4+MjGTx4sU89NBDYcvfffddIiMjKS4u/lcl/TTZ2dmsWbOGZs2aUVZW9m/br4iIiIiIiIiIiIiIiIiI/LZU6qAFm81GixYtrO/NmzcnIyODd95554IHLezcuZNWrVrRuXPnXziV/x7jx48nISHB+t62bVuCwSDPPfccDz/8cNi6M+natSsffvgh69atC5sd4b333qNHjx4sXLjwX5b2H7vzzjsZMGCA9VlERERERERERERERERE5D+dgd4PcTEq7fUQZ5KYmEhCQgIHDhwIW75u3Tr69+9PixYtuOqqqxg9ejTHjh0DYN++faSlpbFlyxYWLFhAWloa3bt3P+s+vF4vTz75JG3atKFVq1Y89thjLFq0iLS0NPbt2xcW7m9/+xvdunUjPT2dG264gUWLFoXFNWbMGG666SZWrVpF7969adGiBbfccgubN28OCxcKhZgxYwbXXXcd6enpXH311bz22mthYc40KKFx48aEQiFyc3N/Mu+qVKlC+/btee+996xlW7duJScnh549e54W/p133qFfv360adOG1q1bc+edd7Jx48af3E9+fj7jx4+nU6dOpKen06dPH7788suwMDbbr6paiYiIiIiIiIiIiIiIiIjIr9Sv6tfloqIi8vLySE5OtpatW7eOO++8k5iYGJ599lmeeOIJNm3axP333w9AjRo1mDt3LikpKWRkZDB37lyef/75s+5j8uTJzJkzh8GDB/Pss88SDAaZPHnyaeEeeOAB5s6dy913381LL71E586defjhh1m2bFlYuNzcXJ588kkGDRrEc889R1lZGcOHD8fn81lhnnrqKaZOnUrv3r3Jysri5ptvZtKkScyePfuc+ZGdnY3L5QrLj3O56aabWLJkCcFgEDBfDdGqVSsSExNPC7tv3z569+7NlClTmDRpEklJSdx+++3s2rXrrPF7vV7uvvtuli5dysiRI3nxxRepX78+Q4cOZfv27eeVRhERERERERERERERERGR/0SGUXl/v2WV+noIAL/fD8CRI0f461//SlRUFP3797fWT548mfT0dJ5//nmM8txu1KgRN910E8uWLSMjI4MWLVrg8XhISEgIe93Ej508eZLZs2dz3333MWTIEAA6d+7MXXfdxcGDB61wK1eu5NNPP2XGjBl06tQJgI4dO5Kbm0tmZiYZGRlW2Ly8PGbNmkXDhg0BiIiIoH///mzYsIFWrVqxZ88eZs2axYQJE7j11lsB6NChA6WlpUybNo1bb731jDMT5OTkMHPmTG677TaioqLOKy979OjBY489xqpVq2jXrh2LFy/mvvvuO2PY4cOHW5+DwSAdO3Zk48aNvP322zz44INn3GbRokVs27aNBQsW0KBBAyv/du/ezQsvvMCUKVPOK50iIiIiIiIiIiIiIiIiIiJQyTMtFBcX06RJE5o0aUK3bt344IMPmDhxIvXq1QOgpKSE7Oxsrr/+egKBAH6/H7/fT0pKCklJSWzatOmC9vftt99SVlbG1VdfHbb8x9+XL19OfHw87dq1s/bp9/vp0KED33zzDYFAwApbo0YNa8ACYP2Yf/jwYQBWrFgBwLXXXntaXLm5uWGDJSoUFhYyYsQIkpOTGTVq1HkfX3R0NF27duXdd99l7dq1HD16lOuuu+6MYb///nuGDRtGhw4daNy4MU2aNGHXrl3k5OScNf7ly5fTqFEjUlJSTjuWCy0LERERERERERERERERERGRSp1pwePxMGvWLEKhEDk5OUyePJk///nPLFq0iBo1apCfn08gEODpp5/m6aefPm37M/3gfy65ubkAVKlSJWx51apVw76fOHGCkydP0qRJk7PGU7NmTQBiY2PD1jmdTgDKysqsuEKhEO3atTtjXAcPHqR27drWd6/Xy7Bhw8jLy2Pu3LlERkae7+EB0LNnT8aNGwdAp06diI+PPy2fCgsLGThwIAkJCYwZM4ZatWrhdrt59NFHrXSfyYkTJ9i6desZ88Vut19QOkVERERERERERERERERE/pPYfuvvaagklTpowWaz0bRpUwCaNWtGamoqffv2Zdq0aUyYMIGYmBgMw2Do0KH06NHjtO1/PPjgp1SvXh0wf3xPTEy0lh87diwsXFxcHAkJCWRlZZ0xnoSEhPPeZ1xcHIZh8NZbb1kDGn4oNTXV+hwMBnnooYfYsmULb775JklJSee9nwpdu3bF7/czf/58Jk6ceMYw69ev59ChQ7z00ktcfvnl1vKCggJrMMbZjiUtLY2nnnrqgtMlIiIiIiIiIiIiIiIiIiLyY5U6aOHHmjZtSs+ePZk/fz7Dhw+nevXqtGjRgp07d1qDG36Ohg0b4na7+fjjj8N+rP/444/DwnXo0IFXXnkFp9MZFu5itG/fHoCTJ0/SvXv3c4adMGECn332GTNmzCAtLe2i9ud2u7n33nvZuHHjaa+9qFBaWgoQNogiOzub/fv3h73q4sc6dOjAsmXLqFGjRtigDxERERERERERERERERGRS50mWrg4v6pBCwD3338/ixcv5vXXX+ehhx7ikUceYcCAAYwcOZKePXsSGxvLoUOHWLFiBX369KFt27bnHXeVKlXo168f06dPx+1207hxY5YsWUJOTg5gzvwA0LFjR7p168bgwYMZPHgwaWlplJSUsGPHDnbv3n1BMw2kpqZy++2388gjjzBo0CCaN2+Oz+cjJyeHVatW8cILLwAwffp05syZw6BBg3C5XKxfv96Ko0GDBkRHR5/3PocMGXLO9S1atCAyMpIJEyYwZMgQDh8+TGZm5k8OROjduzdz5syhf//+DBw4kJSUFAoKCti6dSs+n4/Ro0cDcPz4cVavXm19LioqYsmSJQBkZGQQERFx3sciIiIiIiIiIiIiIiIiIiL/uX51gxbq1avHjTfeyOzZsxk6dCgtW7bkrbfeIjMzk7Fjx+Lz+ahZsybt2rWjbt26Fxz/6NGj8fv9ZGVlEQwGueaaaxgyZAiPP/44MTExVripU6eSlZXF7Nmz2b9/PzExMTRs2JA+ffpc8D4fffRRUlNTmTt3LtOmTSMqKorU1FSuv/56K8zy5csBmDFjBjNmzAjbfubMmRc0OOOnVKtWjSlTpjBx4kTuv/9+UlJSmDBhAq+88so5t3O5XMycOZPMzEymT59Obm4u8fHxXHHFFfzxj3+0wn333Xc88MADYdtWfP/kk09ITk7+xY5FREREREREREREREREROTXQDMtXJxKG7QwYsQIRowYccZ1kyZNCvvetGlTsrKyzhnfggULzmu/LpeLcePGMW7cOGvZww8/TO3atcMGLbhcLoYPH87w4cPPGtczzzxz2rLY2Fi2b98etswwDO644w7uuOOOs8b1xhtvnFf6z+TTTz895/rGjRuflqYuXbrQpUuXsGUZGRlh389URtHR0YwdO5axY8eedX9t27Y9bX8iIiIiIiIiIiIiIiIiIiI/9qubaeFfbfXq1WRnZ9OkSROCwSBLly5l0aJFjBkzprKTJiIiIiIiIiIiIiIiIiIickm55AYtREZGsnTpUl5++WXKysqoXbs2Y8aM4a677qrspImIiIiIiIiIiIiIiIiIyG+Ugd4PcTEuuUEL6enpzJkzp7KTISIiIiIiIiIiIiIiIiIicsm75AYtiIiIiIiIiIiIiIiIiIiI/NIMTbRwUWyVnQARERERERERERERERERERG5NGnQgoiIiIiIiIiIiIiIiIiIiFQKvR5CRERERERERERERERERETkZzL0foiLopkWREREREREREREREREREREpFJopgUREREREREREREREREREZGfSRMtXBzNtCAiIiIiIiIiIiIiIiIiIiKVQjMtiIiIiIiIiIiIiIiIiIiI/EyGplq4KJppQURERERERERERERERERERCqFBi2IiIiIiIiIiIiIiIiIiIhIpdDrIURERERERERERERERERERH4mvRzi4mimBREREREREREREREREREREakUGrQgvxmGcWpsUs4Tn58xzMoNHxIiaH0vDZZan102t/V52fjnOOnLo0acx1pWzZVAnCOWYChEabCUsqAXf8hnrQ+EAsQ5YnDbXPjKlwcJ4ra5wtJQumIvcY5Y7J0vIxAKAFDLk0TwZBF2w87Wwm1W2ENlh8Fpx27Yue6qZEK+AK7y+JZNegEbNp7Im8w8/0J8IZ/1HWBncY4VfzAUYsvuEwRDoTPmS19HLyJdDivdADH2GACSo5KxG3bu6deCG1rXAcCGLSzv7IadsqAXck6GxZvgrEKQIC6by8r3vo5eAFy74ElsPyizV+dvwmP3UOAv5Po5T1EUKDqVFkc0dsOODRt2ww7AtAmfMM+/EFvdWAA6/7F/2L6dhhPDMDjuO8ETDe/CwEapN0BpoIxa7iTyi31W2j02D0GCfDH/LQCKAkVE2aPC4qsXmXIq7kZJNIqqT013IgDDs3rjsrmwYWN3yV4rXJAg8c54AGIdsdbyZU9OpdfiSdiw0bJBNWw/aGrdTruVt7bYSE7m5RJpj7DWe2we3LFmXf1b+nNheWrDRg1XNZ65fCD4zPy2GQZOmw2CIeyGHYfhxFb+z1nfTL8/57hV9rsOFwBgOOxh+wW49s0nmOdfaMYb48YW4SZIkIErp1GWXwg2A5/fy+V148Fu46E9fyHPl0+8M86qnzbDRuPoRgRCAat+AgxcOY3hWb0JhUJWWQNWvdm654RVX1wxbgKhAE7DaW1fFvQSKvMRJGiWfflYxQi7mVffF+dY52KwPE4Dw6pP1IkDwBv0mmVsOHkibzIGNjbsPAbAF/NmhZ0jNmz0dfSy0nXwRIm17nhBqZX+9q1vpK+jFx3ubcOaWRsIhsz9HzpRbOWB3bBb5QjgtDkIhALYsJ3WhlTkTcXyCHsEdTzJxFStbqXPbXPhMJzYDTu+oN/cMLcYl/GDPAiWtwcOG5fXjSfPn0+1OI+VP/HOOGufMRFOpnR/1axDV1S36qijPP+qxpxqPyukRTW08jI1oq61PNLtoLDoJHbDHtZub3nydQAaxDQw884fMNPkqgqA4fzBsQC+kI+QL2CeE047vXo3oSzoxW7Y8W87hsfm4aGcsQC8/8VOMw5sGB4nuw6Z9Ry7jY1zN4XluyfeA1XMtr/AXwhAxp/utcLElZ/Lxo+POWDmW54vH8MwePGqe3l+4HxrteGwY7gd+N/Zbu7asFt1ONIewZpZG3AmV6OvoxdlQS/RDatysOwwYJ73QW+AUPGp+mc37LhtLqss/IdP4qyXaK2rqNu7SnbjtJ06V5aNfy6szSkOlOBslESHjmb9y/fn88VbM631LsNl1U2n7dQEXL6QD4/DzKdc71Gmjf2AIEG27jkBmHUsxhWDw24jeLzwVD4FgwQJsuyFLHCa5/pJXx5UjcBmGAxcOQ2PzYzXHwqE1eG+jl4cKD1IqTdA4Eg+oWAIGzaCwaB1fSg9WcpNbS/jg7X7KAoU4bF7OPSpWf4/bHcqzpWKMqjIL7fTvJ7ZsFlh/OXbxP3hCrzBMuvcMwwzHyvq+vLP5oeFP3iiBKfhpPS5Feahh0LWdfjr3K8JhUL8rn1ds55FmemwYSPCFonb5rLS5m6cTIwjmv25RRAIciIvl0dq347T5gxrR3/4uYLdsONyenAaTspCZvsWCoUwsEHtGIoCRcQ74xgx8xbruGa+942VXpthECz/B2b9z7h3sJlW41Q98n69v3yZeU7X8SRT051ofS8rb1vNRNnAbuANellzfC1gngP+QMhKc8WxTxv3EQDVXdUoT7x5vd50MKwP0SDxcnN1sZdrZj1Og6hUHPWrc2zn8bD8qDgOr7csbHmRv9jcZ8CsS4FgiNKAeW6VeP3UjTD7Pz+87gC8eNW9Yd/xB/G4zDpkxETg6VIfm2Gjovt1sOzwqWt2UjTOeolWPQsFQkTZozBqmP2Px1JP9Wt+eM4CBA8VEu+Mo/1VNwBY11hf0Ecwt8BqZ0KlPnzlx1QcKMEdZ7ZbK7d+Ql9HL7ZnH7DitmEjz59fXh6R1vnSsGUtigMl1vUxUJ6nETYP9SNTATi5eh+h7cesPKqoi95gGY2jG5mJPmL2604cKTp1jQ+G90sDFe1okfe0+hxhd5ttY0R5GZwoZdX2z4BT7fKaWRvI8+eTWisWw25Y1y6Aw2VHCBIk0n3qXCMYxPA48dg8Vjk8l/EKnfvdCYDLcao/0vbyROu6HCTId8e3W32iinoFMG3iMtw2Fyd9J820OWOsNq3t5WYbXXGu2QwjrC0as+1VqzwDwVPtVITdU14vzXOlxBvAwMYV0ZfjSKoCmOdNRZ5VcyVY8YB57auwsWALAMmeWla6bFFuNh07dS0MlfqwxYT3AQ1suGwuRif90co/A1vYvUVFPlT0j0IEoWb0aXnkC/nMdgCzXY+yRxH79A1WmwoQ74gnyh6F03DyaNwoypZ+b9VBe7VTfeqSQJnZx395dXk/0+DAnpPYYiPZV3rACvfDc6jT726z8hwgLTaNQPn1poI36AW7YZ5TRWXc9bsm1r1J/qGDFAWKMAyDjJH3EvIHrOPr6+gF8afuH2f8YyP+kFleTpszrI9bUX/SohpS5C/CwEYgVB5XrFlHfpimU4Vhtn0hr5+0B9rxXLcZQPk1oHpkeR77Tx233QwfaY+AQAiP3U2UPYo8fz5X/f73BAhw1HvMit5uOKy6VJHWTjf0Bcx+USAUwBZt9heX/feztE6rTpsrahAIBfDYPYRCIfo6euGOdWM37Fz75hMAFPqLT+UtmNf+8nRVcyWEHavdsBMkyLSH36f+ZfFWflWPN+vlcZ/Z16j5/3pRFDjVpgQJEvIH8YV8BAtLrPbHZhjEOKIJ5Jttf/BIobX/ij64w+MkRJBg+b1IRZ4a5fdNuBwYjlP1yF4thpJgMeSV4b4yBV/Ix6qd4c8gYqNcZpkbNgzDwBfyn+rLRptlvCF/M54u9cPK++gu8/hCfrNeVY114wv5ibZH0WvxJByGE+cP0lLgLwSPg1CxF8OwEeE61V8z3Ga9CxEkxhGNDRtR9kgK9x+yyrj0O7NdNzynrnFWG2w/1R8q9QUo9gbYeuMMK7/Lgl6rP2B4zP0uy3yJtNg0QiGzD1vRp/phGftDAWyGEXbPb8NGTFJNOFp+T+Ww8bf053A5zT5enchkK5+suMr8GInmdTNYWIov5Au7pwKw14ixzvcYR7R1n4w/SO8OKda5aDfsHJi/1Yw26LXat4p2r+L+kvK8d7hcp+LEbKt/WI7+bcfYfaSAIEFKA2XsPlJgXeOt8ol0Wc8JyoJefDvNvr/bGX7uR7gdYfeER33HwGaw+4j5DClUUsay8c9hT4rHiHHhdtoJhUKceOcbq6x+fF3dm1tIX8epc6gs6MVWNRrDMNtpV7zn1P0i4e3R6KQ/8uHafWHxXdmgGnHOU3k9sep/4992LCwMwRBuh806z76Y8wbTxn1EWdBL4EQhBEPc9bsmXH5fa3xBv9W2Bgma93FRbkI/uO44GyZy6HixFaaiD1nRb7vq97+3wgZCgVN9Ek7V8YpnHqW+U215grPKqTTbbTjLn6H8+L48GApR4vXjtrkwPM6we1s4dS/54zwMEcQW6SbGEY3H5jnV97UZ1vMP85lbGQQhyh4Vdtyu8vYDm8GxgjIyRt1HIBSgOFBinZcVcVSUR8gbsO4vKtrM6x/uBMA/7nnHPM89DqsdqLjHdBpO1szaAJj9lwi3g+JACT3feYbiQAllQS9Ow4k36OW5bjPYW7oPX9BHabCUQCjA5CbP4ra58FRNIFRSBsEQgVDAiv9k0Q/uEX7AcDnM/35afm8Gp66bVv7/oH7aHDaO+o5ZeV7gL8SwG0z9/VvhZWAz+Dr3a+t5X7VYD4ZhEAgFrDz+4bly3VVmu+OoXz2sHCvKqWKbsqCXUKkPfIGwNmrYyE4EisznxxgG8/wLT/WdytuSH96rV9TjYm/Aun6GfH5yvUfDjqM0WErIe+rZgOF2UOwN4Ch/xgdm+YfK+9a+kI94Zxxum4vcFz8h0hZhHUuZN8CqHctwGk78R/LL71vM594VeR7hshMoMsuU8vvDHx5nRR8esJ4bVxxPX0cvQqW+U8+ngyGm/eXD057PAbxz7YNh+Wp4HAQOmdfr2Uu/p23DrmH5kPE/V1ufX3oj2/pccT8+z7/QOgYjxo0v5OOo99T9odNw4nHZ8YX82OI9FAWKSHTXsNb/sM6t3/kV3mCZlbct/pBuras4NrfNZd63BkPh9412W9iziIpj9rjs1Gt8JWVBL+tmb7TSBBA4aNbltUezreefFc+C4xyxBEKB0653DruNEEFyv9iNYRgMz+pNrCPaOocB634QzD5ZSfm5aDfstGtsHru7XT2OHDb3HwwFcZS3C/k7jllp2Pl5DoFgEJuB9cygIj2+kC+s/f4hqzx+8P/Lf1gmR33mdaOiPfUFQqf9BmGFPX7Q/OALUutN81pdx5N82vMugKJPt1j3Gnn+fPyhgJWPFcqCXvo6ejHPv5BkTy0zX6rFcKKwzApXIz4i7PgqjrFinwY2Mh68n2kPv/+D9SGKAyVUjfWY/Yv1h9m5J89abz17t5v3mQ/t+QuhYrPd67V4Ek7DafY1Qua1/HDZESC83pFfdub7BvnVMwyj0v5+yzRoQURERERERERERERERERERCqFBi2IiIiIiIiIiIiIiIiIiIhIpXD8dBARERERERERERERERERERE5l9/4WxoqjWZaEBERERERERERERERERERkUqhmRZERERERERERERERERERER+Jk20cHE004KIiIiIiIiIiIiIiIiIiIhUCs20ICIiIiIiIiIiIiIiIiIi8nMZmmvhYmimBREREREREREREREREREREakUGrQgIiIiIiIiIiIiIiIiIiIilUKvhxAREREREREREREREREREfmZ9HKIi6OZFkRERERERERERERERERERKRSaKYFERERERERERERERERERGRn8nQVAsXpdJmWsjMzCQtLc36a9u2Lf369WPZsmUXFd/evXsZMGAAV155JWlpaXzzzTe/cIr/tVasWMGoUaPo3r07zZs358Ybb+SVV17B5/P95Lbdu3cnLS2NSZMmnbYuJyfHyuNVq1ZdUJoyMzO58sorL2gbgDlz5jBw4EA6duxIy5Yt6du3Lx9//PEFxyMiIiIiIiIiIiIiIiIiIv/ZKvX1EB6Ph7lz5zJ37lyeeOIJysrKuPfee8nOzr7guKZMmcLevXuZOnUqc+fOJSUl5ZdP8L/QnDlzKCoq4k9/+hNZWVn07t2bzMxMHnvssfPaPjIyksWLF5+2/N133yUyMvKXTu45TZ8+nVq1ajF+/HhrcMqwYcN4++23/63pEBERERERERERERERERGRX7dKfT2EzWajRYsW1vfmzZuTkZHBO++8Q8uWLS8orp07d9KqVSs6d+78C6fy32P8+PEkJCRY39u2bUswGOS5557j4YcfDlt3Jl27duXDDz9k3bp1YbMjvPfee/To0YOFCxf+y9L+Y/Pnzw9Lb8eOHdm/fz+vvvoqN998878tHSIiIiIiIiIiIiIiIiIi/y56O8TFqdSZFn4sMTGRhIQEDhw4ELZ83bp19O/fnxYtWnDVVVcxevRojh07BsC+fftIS0tjy5YtLFiwgLS0NLp3737WfXi9Xp588knatGlDq1ateOyxx1i0aBFpaWns27cvLNzf/vY3unXrRnp6OjfccAOLFi0Ki2vMmDHcdNNNrFq1it69e9OiRQtuueUWNm/eHBYuFAoxY8YMrrvuOtLT07n66qt57bXXwsKcaVBC48aNCYVC5Obm/mTeValShfbt2/Pee+9Zy7Zu3UpOTg49e/Y8Lfw777xDv379aNOmDa1bt+bOO+9k48aNP7mf/Px8xo8fT6dOnUhPT6dPnz58+eWX53UsR44c+cn4RURERERERERERERERETk0vGrGrRQVFREXl4eycnJ1rJ169Zx5513EhMTw7PPPssTTzzBpk2buP/++wGoUaOG9TqIjIwM5s6dy/PPP3/WfUyePJk5c+YwePBgnn32WYLBIJMnTz4t3AMPPMDcuXO5++67eemll+jcuTMPP/wwy5YtCwuXm5vLk08+yaBBg3juuecoKytj+PDh+Hw+K8xTTz3F1KlT6d27N1lZWdx8881MmjSJ2bNnnzM/srOzcblcYflxLjfddBNLliwhGAwC5qshWrVqRWJi4mlh9+3bR+/evZkyZQqTJk0iKSmJ22+/nV27dp01fq/Xy913383SpUsZOXIkL774IvXr12fo0KFs3779nGlbu3Yt9erVO6/jEBERERERERERERERERH5zTGMyvv7DavU10MA+P1+AI4cOcJf//pXoqKi6N+/v7V+8uTJpKen8/zzz2OUZ3ajRo246aabWLZsGRkZGbRo0QKPx0NCQkLY6yZ+7OTJk8yePZv77ruPIUOGANC5c2fuuusuDh48aIVbuXIln376KTNmzKBTp06A+YqD3NxcMjMzycjIsMLm5eUxa9YsGjZsCEBERAT9+/dnw4YNtGrVij179jBr1iwmTJjArbfeCkCHDh0oLS1l2rRp3Hrrrdhsp48dycnJYebMmdx2221ERUWdV1726NGDxx57jFWrVtGuXTsWL17Mfffdd8aww4cPtz4Hg0E6duzIxo0befvtt3nwwQfPuM2iRYvYtm0bCxYsoEGDBlb+7d69mxdeeIEpU6acdbt169Yxbdq08zoOERERERERERERERERERG5NFTqTAvFxcU0adKEJk2a0K1bNz744AMmTpxo/Y/8kpISsrOzuf766wkEAvj9fvx+PykpKSQlJbFp06YL2t+3335LWVkZV199ddjyH39fvnw58fHxtGvXztqn3++nQ4cOfPPNNwQCAStsjRo1rAELgPVj/uHDhwFYsWIFANdee+1pceXm5oYNlqhQWFjIiBEjSE5OZtSoUed9fNHR0XTt2pV3332XtWvXcvToUa677rozhv3+++8ZNmwYHTp0oHHjxjRp0oRdu3aRk5Nz1viXL19Oo0aNSElJOe1YzlYW27Zt47//+7/p06cPPXr0OO9jERERERERERERERERERH5LTEq8e+3rFJnWvB4PMyaNYtQKEROTg6TJ0/mz3/+M4sWLaJGjRrk5+cTCAR4+umnefrpp0/b/kw/+J9Lbm4uAFWqVAlbXrVq1bDvJ06c4OTJkzRp0uSs8dSsWROA2NjYsHVOpxOAsrIyK65QKES7du3OGNfBgwepXbu29d3r9TJs2DDy8vKYO3cukZGR53t4APTs2ZNx48YB0KlTJ+Lj40/Lp8LCQgYOHEhCQgJjxoyhVq1auN1uHn30USvdZ3LixAm2bt16xnyx2+2nLdu/fz/33HMPzZo14/HHH7+g4xARERERERERERERERERkf98lTpowWaz0bRpUwCaNWtGamoqffv2Zdq0aUyYMIGYmBgMw2Do0KFn/F/6Px588FOqV68OmD++JyYmWsuPHTsWFi4uLo6EhASysrLOGE9CQsJ57zMuLg7DMHjrrbesAQ0/lJqaan0OBoM89NBDbNmyhTfffJOkpKTz3k+Frl274vf7mT9/PhMnTjxjmPXr13Po0CFeeuklLr/8cmt5QUGBNRjjbMeSlpbGU0899ZPpOH78OIMGDaJq1ao8//zzZzx2ERERERERERERERERERG5tFXqoIUfa9q0KT179mT+/PkMHz6c6tWr06JFC3bu3GkNbvg5GjZsiNvt5uOPPw77sf7jjz8OC9ehQwdeeeUVnE5nWLiL0b59ewBOnjxJ9+7dzxl2woQJfPbZZ8yYMYO0tLSL2p/b7ebee+9l48aNp732okJpaSlA2ECC7Oxs9u/fH/aqix/r0KEDy5Yto0aNGmGDPn6sqKiIe+65B5/Px8yZM4mOjr6oYxERERERERERERERERER+a0wfuvvaagkv6pBCwD3338/ixcv5vXXX+ehhx7ikUceYcCAAYwcOZKePXsSGxvLoUOHWLFiBX369KFt27bnHXeVKlXo168f06dPx+1207hxY5YsWUJOTg5gzvwA0LFjR7p168bgwYMZPHgwaWlplJSUsGPHDnbv3n1eMw1USE1N5fbbb+eRRx5h0KBBNG/eHJ/PR05ODqtWreKFF14AYPr06cyZM4dBgwbhcrlYv369FUeDBg0u6If/IUOGnHN9ixYtiIyMZMKECQwZMoTDhw+TmZl5zoEIAL1792bOnDn079+fgQMHkpKSQkFBAVu3bsXn8zF69GgARowYwbZt23jqqac4cOAABw4cCNu3iIiIiIiIiIiIiIiIiIgI/AoHLdSrV48bb7yR2bNnM3ToUFq2bMlbb71FZmYmY8eOxefzUbNmTdq1a0fdunUvOP7Ro0fj9/vJysoiGAxyzTXXMGTIEB5//HFiYmKscFOnTiUrK4vZs2ezf/9+YmJiaNiwIX369LngfT766KOkpqYyd+5cpk2bRlRUFKmpqVx//fVWmOXLlwMwY8YMZsyYEbb9zJkzL2hwxk+pVq0aU6ZMYeLEidx///2kpKQwYcIEXnnllXNu53K5mDlzJpmZmUyfPp3c3Fzi4+O54oor+OMf/3jasfz5z38+LY7t27f/YschIiIiIiIiIiIiIiIiIvLroakWLkalDVoYMWIEI0aMOOO6SZMmhX1v2rQpWVlZ54xvwYIF57Vfl8vFuHHjGDdunLXs4Ycfpnbt2mGDFlwuF8OHD2f48OFnjeuZZ545bVlsbOxpP8wbhsEdd9zBHXfccda43njjjfNK/5l8+umn51zfuHHj09LUpUsXunTpErYsIyMj7PuZyig6OpqxY8cyduzYs+5PAxNEREREREREREREREREROR8/OpmWvhXW716NdnZ2TRp0oRgMMjSpUtZtGgRY8aMqeykiYiIiIiIiIiIiIiIiIiIXFIuuUELkZGRLF26lJdffpmysjJq167NmDFjuOuuuyo7aSIiIiIiIiIiIiIiIiIi8htl6O0QF+WSG7SQnp7OnDlzKjsZIiIiIiIiIiIiIiIiIiIil7xLbtCCiIiIiIiIiIiIiIiIiIjIL00TLVwcW2UnQERERERERERERERERERERC5NmmlBRERERERERERERERERETkZzI01cJF0UwLIiIiIiIiIiIiIiIiIiIiUik0aEFEREREREREREREREREREQqhV4PISIiIiIiIiIiIiIiIiIi8rPp/RAXQzMtiIiIiIiIiIiIiIiIiIiISKXQTAsiIiIiIiIiIiIiIiIiIiI/k6GJFi6KZloQERERERERERERERERERGRSqFBCyIiIiIiIiIiIiIiIiIiIlIp9HoIERERERERERERERERERGRn0lvh7g4mmlBREREREREREREREREREREKoUGLchvRiAUAKCWJ4lNn3xwxjDtW15PHU8yf2s+NWybH35O9tRinn8hnf7rNr7+5HuO+06Y8bqTyPPnA1DdVQ27YadpfFP6OnoBkOs9yjeF3+IPBay40qIaUsVZJSwNCb0bU8tTEw4V4rF5AIi0ReCoU5VAKEDz2KZW2BhHNIEjeTgNJ//4Yif2KtHkeo8C0GXgQNJjGlthG0TWI0iQaZM+t/Ih0h4BQGrkZUyoP4AE16m07CzOsT7P8y8kEAwRCoWsZXHOWADWHF9LdVe1sGNw2VwA1rEXB0rMMMmxYeF8IR8JziqUBsrC9gWw6L8eoThQYi1f0vf/4TQcRNojODn+E9JjrrDy0Rf0s6N4JzGOaBpHpxFpj2DZE1MAKPtoB2VBL5ePbFeeZzEkOKtw3HcCt82F03DS+Zbb2Vu6j8uqR1Enojbx6Q2IjXRaeVzFGYfTcGIrb/LSY66gNFgKmGX9XKcsdhTvtNJauPF7ql7eiEh7hJXHcc5YXDYXqRF1rXDVXdVIdFUHsOIDyBg/krzdJzAMczxdbU8ta93RvFLinXEA2OIjqdYy3doHgN2w06O9uY8HN4+08jTC7ibKEcn+0kPM8y/EXjeO6q5qFAdKiPQ4wOXEYdiJsLtx2hwECULQLG/X9Q2JcUQDkJoYY+ZraTF2wx5WnoNvbW59NuI9BAvMct/8hzfxJFWjpLCAmG5NKC71Eyouo6+jF6XBUqo44qnlScIX8lHgL8DARk13IgX+QupG1MFpc7D5D29WxMyO4p1WHpQFvcQ4ovnwtnkU+AsBeOfaB4lxROO0Oax014tMAcPAaTiJc8bgLq+jJ3x5ALR6ZCD+8vpUUc7HvMcJhALYDTuuODdR9iiCBDE8TutcDxGkeb2qZrmNe4AoZzRb95yw6s48/0KinGYaojwOouxRAES6HVb6Xbc1ZZ5/IU9fPhAMw8rX1JqxRNojOFFYxklfnnVuABT4C/GXp+3H51+sMwabYeAL+oi0R+ANermsU1uC+SXU8SSbZWpzEeOIJsLutrYLrD2IrXz/TsOJkWC2P/iDFJf6qe6qxpETJZz05fHmx99RxRFvbVvi9bP883coDpRQ+tZmGkTWK9+PGf8/v9xlhfWFfARLvMTGJpj5bRiUhbzW+r1HC9lXesBs30IBK80p0akAuJtdhtNwkluaiw0bpQHz3AmVBcLOo3hnnNUmHs0rZdm6A9SLTCEYCuHochmXRdSmr6MXtgg313RIsbYLFZWRWtOs54FDJ6n3O7MdddtcFAdK8BX7CLy3g6Pe40TYIygJFhPd3dw+yh5Fots8p+1148LKZc2B1YB5rleU5/BX+wDgNJz4DxyHYIiEB9oCZv2pqL8NmrYGw+Dorp1WPXiv9xhOltffplWbYo9wENhz8lR5hgLEO+NJdNfAY/Ow9chmln/+DgAnfXkc9h4BzGtalRtaAhAMBcPqWXGgBI/NQ+HG71mx3FzeqHpjMv4ygr6OXsQ5YtlfesDapix4qhxLAiXke8301fEkE5uRQoG/kA9vmwfAVXEtWHMim5xD+djiozhcZqYHmw0bNjr1vJVgfglRjkjaXd4dV+0YYhwxHDlcaJWzp0YCgVDAbK8w27oYRzSXVY/i5MED4Ata14koRyQb8jcRl2yWy3VXJZMaURen4aD73S0p8BcSaY/AY/NwuOxI2HWpojwAvrz9H6RFNeSKmMut9twbNMPmbz9KrDueg2WHrTIoDBSxveg7c59vPQFgXUujPA5qeWriblsXp+GkNFgaVoeviLkcgFYJVxHYZZZtgiueOq2v4rjvhNUO+Q/l4Qv5KfMHwGZQtfZlZIx74FS5ludPRXr/1nyq1c+p2J/T5uBA6UHAbB9Kg6UQa14j0+qZ8VT0d/r3NM+JRlH1+XbfSTw2j1UXXTYXoSIfxYES7Jy6RsSP6RyWn5d1aktSzVSM8va2om0EsMVGQiBEUlwyraqY+27QtDUOu2FdN9JjGhMkyLAnriHSHoHT5iSvyEvZmxtoEFmPQydLrD6E2+Zix+FtgNl23nNbC74p/JYvF83h00GPh5ez3Tz3nYbD6sNU5GGu9ygYBrU8NSkt81vxOx02jvtOUNOdiN2wh/Udu9w5IKxMl41/jpIyPzZsBI8XEjhYSB1PbT7/ZAdfbj4Y3tYbsPzzd6z4QgVefCEfjsvNa06zmCZh6YNT/S5bvIf6kak4W9Yi0h5BnCOWCHsE0VUSCIVOtTNGrIeiUj9VXQm4bS7sLvPa1PmW25nnX8in9zxOVZfZVhuGQfuW1wPgsbmp7qpGlD2K2tWiqONJJhgKcaKwDGfLWmTcdw+FgSIib2iK3bBT75oGxGSY9a8wUER6zBUkOKsQ64636sCy/8kEILZaJDU9iZQFvRi28P9X4LDbiHfGsze3iCh7lHWtAUhwVsFpc5CbV14u6TW4Kq6FGWd0FfPaahhUq1GH3blFhMoCYdeuin5HSZkfgAh7BNhsHD12AG/QS5wjFhKjWLF8IWkj2wOQV3SqndibW0icIxajvK9RcU6A2RZU9OkDy/eFtZVHvccJYrYJPr9Z1vHOeMDss566f6nJV1lrAIhzxGK3QaK7hpkvNeIpDZZit0Ger4CqMW5quKsx/uREaz++oB+7YSdI0Lo213Qnkuiugdvmwr/vGADdssYR54ilNFiKL+QDzDamoh5HOSIxotzkfL/ZiruaK4FoRyS+oJ/blpn9b7thx2HYcdtcVr8qEDp1nZ7nX2jeLxT7rXjsht3qAxV7i6xw9SNT8GcfJBAKWH29mlVq07RhW4oDJaTNGYqzRW1iHbEECbJyy8enjjvkw27Y8fRoiN2wU9VZFcNm4EiKp2Gr9la4ijYe4JaXexPjiMYb9NLX0Ys1x9cSaY/AZpyqj2VBLzhsHCw7TLGv2LwmRprnSjAUoo4nmUh7JF9OeZlgcRkNIuthMwzm+RcSXz/BiueDfo8SIkSkPQKX20OSO9E6nytsL/qOhrFm+pM9tfDYPCy77ylO+vLC+nExjmgS3TUI5hbTMKYBgVCAw0cKWfHFAgDqxdTDk2geZ2RCFfo6euGxu8Fhwxsso16tJuAPmvewDc024tjiNfiCPtr/ri+NoxsBcNx7wuqHxzrNNhObgQ0bef58qruqYasSQfqVXZjnX0h+kZeGteIoC3qp7qpGELOv0aN9XfOa3aAqttgIigJmmR/25gLmvSqY99B1PMkUBYqo5krgjfe34TSc1HQnEts9lQPHzXN+2pglfLffPO+chnkfN+yRDFIj6lrpdBpOjAgHie4aGC4nNe7tQTCvyKp30XWrYDMM/Dm5RNoj6OvoRePoNK6b/SSeKhFUd1XDF/JhM8zrUZ4/nwJ/oVlmu05giz11T2bEuM3z3m0HAzw2D22S21vHta/0AKXeAKFQiAOlB7FVj+WymMuonWLms6u+eV/e5upeBA6a9d5b3nZ8cvd4anmSsKWY5RDpdnLUe4w8fz55u09QFCiisMRnpcVpOOF4CbYYD+64GI4cLjC3i4kl5Df7SmVBL0nuROKdcWb73MRsXxtEpRLaa+Zr8GQxR73HmTZxmVUfbLGRVl+9WqwHj9PGI8cmmOuwUcuTRDBk1ulQgZn+q1/9b9YcX4vdZhDpiqI4WILdsBMKhUj21KJ9i+twGHbqRabiNJzU8tSkjieZBlGplB4+ZuapebLx4OaRhEIQ74gnEDDbkzhH7Klrsc1g2BPXmH1+t5NqrqrWddZtc5ntqMNm9d8BiDLrjxHp4o33t1mLK/oBYPZbCgNFxMVWs9o9R7J5fQ4eL6RxdCOOFJn9wejyPo6jRjwACQmJ1IyuiaPLZbw78QvA7I/lF/mg/BkEQMZ99+D7/jB7S/cD5jnhC/iIccTgC5h5WvEcoHbVSKve2w07kfZIfLuOcPiLHJI9tThWcAQbNr5e8T62eLPdiHfG4e50GSGvj7SohlR3VbPukc04zXtZp+HEZXMRaY9gxfKFBIMh4hyxFE1dZYU1DMOqn30dvbht2RSuvSq5vAjMa8CXmw9y1Hucqq4EPDYPtefcjqPLZeVhTrWvdruNAn8hSe5E7s+ezrAnriFECNeVlxHy+unr6EWPK2tb7XtFmZcGS7HXirPaJ4DAwTwuv6yKVd51PMnUjahDtRp1yPPnc2zxGitsdVc1eq585FTfuDw/K/qo+3ILaV2tFS6biyuuvdbaLlRcRpQjsvz6eir/zDKridNho1nilRzIzbGuYRU8Nk/Ysst+cK+en3+cRFcN6ldrRCAUIK12U3y7jljpq3hWRCiEP+TDXiXa6gd6C73ExVbDFh9JlMdBxrC2lAW91PIkcdKXZ9WbZE8tq39vqx6JPxQgz59PkKB5/7jbXGevHWue84Veco8doJYnifSYK4Dy+4PytBjYOFFYRogghduOWnnnsbspC3pZ8cUC6kbUIcYdS3VXNeIcsYzeMgqXzYWzQQ2OFRwBl9PK/xh7NPuPmNeGeGccNmyUlffJDJeTL9+diy02glqepLB+OwAOBx6XHaqY9+s2wyDeEY/b5iLKHmU+87DbsLeuRXVXNepG1CnPzhBpUQ2t6+DB48WUBsuo7qpm9Yl//PwF4MtFc6zrly/ks54t7SrZbS1zXFYNDIPiQImVfwD2KjFmGxgwt7Hao2AIt81NjD0aI9Jl5Ys36MXjtFvP30JeP6kRdcP6MvHOOMryT9UtR6NqlJT56PH3m806EiyjlqcmgSPm/WRZ0Es1Z1Wi7FHEJtey6kgoFCI6wkmMI9p8Tu334525ATBI9tTii03m/WNxWQDDZrb5oRIvJ315JLkTiWxQmxhHNA67zeoL+wJBKw9TI+oyz7+Q4IlTafW47Az7n2utPGpTp4O1ruL+p6L+hwq9eMrvTd/uMYqSQ2YZ1I2oQ19HL47ln+qr/6CZoShQFPYcFcznN9VcCWHPbFtUbc7B48WUBcsw6sWTHnPFGcsfoGWL7tSNuMzK/ynNhwBQJ/Yyq1067juB3bBjOO1WnQOzHfnhs4CK8AePF+PddZjUiLpEtDD7DxV9QXtnc18/7Df2aF8Xj81DLU8Sie4ajNn2KvbyZ1sAH36+y3xOfUV1Ql4/z3XKolrTxmGZU7gl1zqfCvyFOCr6SPYoDh4zz8cvF8zh2ITPAIh0ReGpUv7bQts6HB37oRnRoUKCIbDZbCTUMdPV5c4BVHdVo44n2Wq/PTYPkTHmbwUV+w2FQiS5E600JTir8LfmU/HYPMSXP4cMec1rfkK0mxru6mHnVIXqNc088m7aS943uew7WkRStTpm/7dcHU8yHpeDdfkbcVeJtfaXGlGXhlH1rfshgDa12ll9iIrzzYhx43HarbLbd7SIBpH1wq5FTsNp1VmnzUHz/s0p+/A7a32Bv4D0mCsIlj+DDxX76NyytrVtxb1jqLgMu2Gnr6MXRvkz5bzdJ4i0R2A3HIS8fsqCXiLtEThqVrHyuF5kCv41B0n+wW8L8htiVOLfb5gGLYiIiIiIiIiIiIiIiIiIiEil0KAFERERERERERERERERERERqRSOyk6AiIiIiIiIiIiIiIiIiIjIb53xW39PQyXRTAsiIiIiIiIiIiIiIiIiIiJSKTTTgoiIiIiIiIiIiIiIiIiIyM9kaKKFi6KZFkRERERERERERERERERERKRSaKYFERERERERERERERERERGRn0kTLVwczbQgIiIiIiIiIiIiIiIiIiIilUKDFkRERERERERERERERERERKRS6PUQIiIiIiIiIiIiIiIiIiIiP5ehF0RcDM20ICIiIiIiIiIiIiIiIiIiIpVCMy2IiIiIiIiIiIiIiIiIiIj8TJpn4eJU2kwLmZmZpKWlWX9t27alX79+LFu27KLi27t3LwMGDODKK68kLS2Nb7755hdO8b/WihUrGDVqFN27d6d58+bceOONvPLKK/h8vp/ctnv37qSlpTFp0qTT1uXk5Fh5vGrVqgtKU2ZmJldeeeUFbQPw9ttv07dvX9q0aUPTpk257rrrmDZtGl6v94LjEhERERERERERERERERGR/1yVOtOCx+Ph9ddfB+DIkSNMnz6de++9lzfffJOWLVteUFxTpkxh7969TJ06lZiYGFJSUv4FKf7XmTNnDqWlpfzpT38iKSmJDRs2kJmZyffff8/TTz/9k9tHRkayePFiHnroobDl7777LpGRkRQXF/+rkn6avLw8OnfuzJAhQ4iOjmbjxo08//zzHDp0iCeeeOLflg4REREREREREREREREREfl1q9RBCzabjRYtWljfmzdvTkZGBu+8884FD1rYuXMnrVq1onPnzr9wKv89xo8fT0JCgvW9bdu2BINBnnvuOR5++OGwdWfStWtXPvzwQ9atWxc2O8J7771Hjx49WLhw4b8s7T921113hX1v164dRUVFvPbaa4wfPx673f5vS4uIiIiIiIiIiIiIiIiIyL+DofdDXJRKez3EmSQmJpKQkMCBAwfClq9bt47+/fvTokULrrrqKkaPHs2xY8cA2LdvH2lpaWzZsoUFCxaQlpZG9+7dz7oPr9fLk08+SZs2bWjVqhWPPfYYixYtIi0tjX379oWF+9vf/ka3bt1IT0/nhhtuYNGiRWFxjRkzhptuuolVq1bRu3dvWrRowS233MLmzZvDwoVCIWbMmMF1111Heno6V199Na+99lpYmDMNSmjcuDGhUIjc3NyfzLsqVarQvn173nvvPWvZ1q1bycnJoWfPnqeFf+edd+jXrx9t2rShdevW3HnnnWzcuPEn95Ofn8/48ePp1KkT6enp9OnThy+//PInt4uPj8fv9xMMBn8yrIiIiIiIiIiIiIiIiIiIXBp+VYMWioqKyMvLIzk52Vq2bt067rzzTmJiYnj22Wd54okn2LRpE/fffz8ANWrUYO7cuaSkpJCRkcHcuXN5/vnnz7qPyZMnM2fOHAYPHsyzzz5LMBhk8uTJp4V74IEHmDt3LnfffTcvvfQSnTt35uGHH2bZsmVh4XJzc3nyyScZNGgQzz33HGVlZQwfPhyfz2eFeeqpp5g6dSq9e/cmKyuLm2++mUmTJjF79uxz5kd2djYulyssP87lpptuYsmSJdbAgHfffZdWrVqRmJh4Wth9+/bRu3dvpkyZwqRJk0hKSuL2229n165dZ43f6/Vy9913s3TpUkaOHMmLL75I/fr1GTp0KNu3bz8tvN/vp6SkhDVr1vD666/Tr18/nE7neR2LiIiIiIiIiIiIiIiIiMhviVGJf79llfp6CDB/2AY4cuQIf/3rX4mKiqJ///7W+smTJ5Oens7zzz+PUT6fRqNGjbjppptYtmwZGRkZtGjRAo/HQ0JCQtjrJn7s5MmTzJ49m/vuu48hQ4YA0LlzZ+666y4OHjxohVu5ciWffvopM2bMoFOnTgB07NiR3NxcMjMzycjIsMLm5eUxa9YsGjZsCEBERAT9+/dnw4YNtGrVij179jBr1iwmTJjArbfeCkCHDh0oLS1l2rRp3Hrrrdhsp48dycnJYebMmdx2221ERUWdV1726NGDxx57jFWrVtGuXTsWL17Mfffdd8aww4cPtz4Hg0E6duzIxo0befvtt3nwwQfPuM2iRYvYtm0bCxYsoEGDBlb+7d69mxdeeIEpU6ZYYf1+P02aNLG+33zzzfzlL385r+MQEREREREREREREREREZFLQ6XOtFBcXEyTJk1o0qQJ3bp144MPPmDixInUq1cPgJKSErKzs7n++usJBAL4/X78fj8pKSkkJSWxadOmC9rft99+S1lZGVdffXXY8h9/X758OfHx8bRr187ap9/vp0OHDnzzzTcEAgErbI0aNawBC4D1Y/7hw4cBWLFiBQDXXnvtaXHl5uaGDZaoUFhYyIgRI0hOTmbUqFHnfXzR0dF07dqVd999l7Vr13L06FGuu+66M4b9/vvvGTZsGB06dKBx48Y0adKEXbt2kZOTc9b4ly9fTqNGjUhJSTntWH5cFg6Hg//7v//jzTffZOzYsXz22WeMHTv2vI9FREREREREREREREREROQ3xTAq7+83rFJnWvB4PMyaNYtQKEROTg6TJ0/mz3/+M4sWLaJGjRrk5+cTCAR4+umnefrpp0/b/kw/+J9Lbm4uAFWqVAlbXrVq1bDvJ06c4OTJk2EzBfw4npo1awIQGxsbtq7i9QdlZWVWXKFQiHbt2p0xroMHD1K7dm3ru9frZdiwYeTl5TF37lwiIyPP9/AA6NmzJ+PGjQOgU6dOxMfHn5ZPhYWFDBw4kISEBMaMGUOtWrVwu908+uijVrrP5MSJE2zduvWM+WK3209b1rRpUwBatWpFcnIyw4YN44477rCWi4iIiIiIiIiIiIiIiIjIpa1SBy3YbDbrB+xmzZqRmppK3759mTZtGhMmTCAmJgbDMBg6dCg9evQ4bfsfDz74KdWrVwfMH98TExOt5ceOHQsLFxcXR0JCAllZWWeMJyEh4bz3GRcXh2EYvPXWW9aAhh9KTU21PgeDQR566CG2bNnCm2++SVJS0nnvp0LXrl3x+/3Mnz+fiRMnnjHM+vXrOXToEC+99BKXX365tbygoMAajHG2Y0lLS+Opp5664HSlp6cDsGfPHg1aEBERERERERERERERERERoJIHLfxY06ZN6dmzJ/Pnz2f48OFUr16dFi1asHPnzl/kh+6GDRvidrv5+OOPw36s//jjj8PCdejQgVdeeQWn0xkW7mK0b98egJMnT9K9e/dzhp0wYQKfffYZM2bMIC0t7aL253a7uffee9m4ceNpr72oUFpaChA2iCI7O5v9+/eHverixzp06MCyZcuoUaNG2KCP87F27VoA6tSpc0HbiYiIiIiIiIiIiIiIiIj8Fvy2X9JQeX5VgxYA7r//fhYvXszrr7/OQw89xCOPPMKAAQMYOXIkPXv2JDY2lkOHDrFixQr69OlD27ZtzzvuKlWq0K9fP6ZPn47b7aZx48YsWbKEnJwcwJz5AaBjx45069aNwYMHM3jwYNLS0igpKWHHjh3s3r37gmYaSE1N5fbbb+eRRx5h0KBBNG/eHJ/PR05ODqtWreKFF14AYPr06cyZM4dBgwbhcrlYv369FUeDBg2Ijo4+730OGTLknOtbtGhBZGQkEyZMYMiQIRw+fJjMzMyfHIjQu3dv5syZQ//+/Rk4cCApKSkUFBSwdetWfD4fo0ePBuD222/nmmuuoV69ethsNjZs2MCrr75K586dadas2Xkfh4iIiIiIiIiIiIiIiIiI/Gf71Q1aqFevHjfeeCOzZ89m6NChtGzZkrfeeovMzEzGjh2Lz+ejZs2atGvXjrp1615w/KNHj8bv95OVlUUwGOSaa65hyJAhPP7448TExFjhpk6dSlZWFrNnz2b//v3ExMTQsGFD+vTpc8H7fPTRR0lNTWXu3LlMmzaNqKgoUlNTuf76660wy5cvB2DGjBnMmDEjbPuZM2de0OCMn1KtWjWmTJnCxIkTuf/++0lJSWHChAm88sor59zO5XIxc+ZMMjMzmT59Orm5ucTHx3PFFVfwxz/+0QqXnp7OvHnzOHDgAA6Hg+TkZEaMGBEWRkRERERERERERERERETkP4mhqRYuSqUNWhgxYgQjRow447pJkyaFfW/atClZWVnnjG/BggXntV+Xy8W4ceMYN26ctezhhx+mdu3aYYMWXC4Xw4cPZ/jw4WeN65lnnjltWWxsLNu3bw9bZhgGd9xxB3fcccdZ43rjjTfOK/1n8umnn55zfePGjU9LU5cuXejSpUvYsoyMjLDvZyqj6Ohoxo4dy9ixY8+6v59aLyIiIiIiIiIiIiIiIiIiAr/CmRb+1VavXk12djZNmjQhGAyydOlSFi1axJgxYyo7aSIiIiIiIiIiIiIiIiIiIpeUS27QQmRkJEuXLuXll1+mrKyM2rVrM2bMGO66667KTpqIiIiIiIiIiIiIiIiIiPxm6f0QF+OSG7SQnp7OnDlzKjsZIiIiIiIiIiIiIiIiIiIil7xLbtCCiIiIiIiIiIiIiIiIiIjIL83QRAsXxVbZCRAREREREREREREREREREZFLk2ZaEBERERERERERERERERER+Zk00cLF0UwLIiIiIiIiIiIiIiIiIiIiUik0aEFEREREREREREREREREREQqhV4PISIiIiIiIiIiIiIiIiIi8jMZej/ERdFMCyIiIiIiIiIiIiIiIiIiIpeo77//nrvvvpsWLVrQsWNHJk6ciNfr/cntQqEQWVlZdO3alWbNmnHrrbeyfv36C96/Bi2IiIiIiIiIiIiIiIiIiIj8bEYl/l2cvLw8BgwYgM/nIzMzk1GjRjFv3jyeeeaZn9z25ZdfZurUqdx111289NJLVK9enYEDB7J3794LSoNeDyEiIiIiIiIiIiIiIiIiInIJmjNnDkVFRTz//PPEx8cDEAgEmDBhAkOHDiUxMfGM25WVlfHSSy8xcOBA7rrrLgCuuuoqrr/+embMmMH48ePPOw2aaUFEREREREREREREREREROQS9Pnnn9O+fXtrwALADTfcQDAYZPny5WfdLjs7m8LCQm644QZrmcvl4pprruHzzz+/oDRo0IKIiIiIiIiIiIiIiIiIiMjPZBiV93exdu7cSb169cKWxcbGUr16dXbu3HnO7YDTtq1fvz4HDhygtLT0vNOg10OIiIiIiIiIiIiIiIiIiIj8hl199dXnXP/JJ5+ccXl+fj6xsbGnLY+LiyMvL++s8eXn5+NyuXC73WHLY2NjCYVC5OXl4fF4ziPlYIRCodB5hRQREREREREREREREREREZFfnYsdtNCkSRMeeOABhgwZErb8pptu4sorr+SJJ54443YvvvgiL7zwAps2bQpbvmTJEh544AE+//xzEhMTzyvtmmlBRERERERERERERERERETkN+xsgxJ+SmxsLAUFBactz8vLIy4u7pzbeb1eysrKwmZbyM/PxzCMc277Y7YLS7KIiIiIiIiIiIiIiIiIiIj8J6hXrx47d+4MW1ZQUEBubi716tU753YAu3btClu+c+dOatWqdd6vhgANWhAREREREREREREREREREbkkdenShRUrVpCfn28tW7JkCTabjY4dO551u5YtWxIdHc37779vLfP5fHz44Yd06dLlgtKg10OIiIiIiIiIiIiIiIiIiIhcgm677TbeeOMNhg0bxtChQzl8+DATJ07ktttuIzEx0Qo3YMAADhw4wEcffQSA2+1m6NChZGZmkpCQQKNGjZg9ezYnT55k0KBBF5QGDVoQERERERERERERERERERG5BMXFxfH666/zxBNPMGzYMKKiorjlllsYNWpUWLhgMEggEAhbds899xAKhXj11Vc5fvw4jRs3ZsaMGdSpU+eC0mCEQqHQzz4SERERERERERERERERERERkQtkq+wEiIiIiIiIiIiIiIiIiIiIyKVJgxZERERERERERERERERERESkUmjQgoiIiIiIiIiIiIiIiIiIiFQKDVoQERERERERERERERERERGRSqFBCyIiIiIiIiIiIiIiIiIiIlIpNGhBREREREREREREREREREREKoUGLYiIiIiIiIiIiIiIiIiIiEil0KAFERERERERERERERERERERqRQatCAiIiIiIiIiIiIiIiIiIiKVQoMWREREREREREREREREREREpFJo0IKIiIiIiIiIiIiIiIiIiIhUCg1aEBERERERERERERERERERkUrx/wE/qWYJP5YPYgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 2800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cc.pl.heatmap(adata_cc,rna, rnalabels = [\"Female1\", \"Female2\", \"Female3\",\"Male1\", \"Male2\", \"Male3\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4f3ee4b-9caa-4057-93d8-24ea5638bc71",
   "metadata": {},
   "source": [
    "Find out the co-differential peak-gene pairs. Look into all the differential peaks and then see if the annotated genes are also significantly expressed. We can set the pvalue and score/log foldchange cutoff easily.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ed2f4345-17dd-43cd-aa42-93627776b16a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Peak</th>\n",
       "      <th>logfoldchanges_peak</th>\n",
       "      <th>Pvalue_peak</th>\n",
       "      <th>Pvalue_adj_peak</th>\n",
       "      <th>Gene</th>\n",
       "      <th>Score_gene</th>\n",
       "      <th>Pvalue_gene</th>\n",
       "      <th>Pvalue_adj_gene</th>\n",
       "      <th>Distance_peak_to_gene</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1_174659622_174662521</td>\n",
       "      <td>5.652435</td>\n",
       "      <td>1.530047e-08</td>\n",
       "      <td>4.586591e-07</td>\n",
       "      <td>Grem2</td>\n",
       "      <td>-10.401831</td>\n",
       "      <td>1.280025e-67</td>\n",
       "      <td>1.252748e-65</td>\n",
       "      <td>171264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1_174917639_174921559</td>\n",
       "      <td>6.208699</td>\n",
       "      <td>2.711848e-12</td>\n",
       "      <td>1.562878e-10</td>\n",
       "      <td>Grem2</td>\n",
       "      <td>-10.401831</td>\n",
       "      <td>1.280025e-67</td>\n",
       "      <td>1.252748e-65</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr2_93645657_93648162</td>\n",
       "      <td>5.189615</td>\n",
       "      <td>2.360560e-06</td>\n",
       "      <td>4.324934e-05</td>\n",
       "      <td>Alx4</td>\n",
       "      <td>-10.292504</td>\n",
       "      <td>5.458739e-18</td>\n",
       "      <td>1.081356e-16</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr3_33140350_33142508</td>\n",
       "      <td>5.534632</td>\n",
       "      <td>6.455627e-08</td>\n",
       "      <td>1.724615e-06</td>\n",
       "      <td>Pex5l</td>\n",
       "      <td>-7.590236</td>\n",
       "      <td>2.351122e-24</td>\n",
       "      <td>6.841972e-23</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr3_126498429_126499612</td>\n",
       "      <td>5.337659</td>\n",
       "      <td>5.594815e-07</td>\n",
       "      <td>1.202787e-05</td>\n",
       "      <td>Arsj</td>\n",
       "      <td>-6.281259</td>\n",
       "      <td>8.667831e-27</td>\n",
       "      <td>2.783525e-25</td>\n",
       "      <td>-58056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>chr3_126657669_126660188</td>\n",
       "      <td>-5.397757</td>\n",
       "      <td>5.546104e-07</td>\n",
       "      <td>1.202787e-05</td>\n",
       "      <td>Arsj</td>\n",
       "      <td>-6.281259</td>\n",
       "      <td>8.667831e-27</td>\n",
       "      <td>2.783525e-25</td>\n",
       "      <td>-217296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>chr3_132085669_132092999</td>\n",
       "      <td>6.121213</td>\n",
       "      <td>1.509244e-105</td>\n",
       "      <td>2.850264e-102</td>\n",
       "      <td>Dkk2</td>\n",
       "      <td>-6.916087</td>\n",
       "      <td>9.389039e-178</td>\n",
       "      <td>5.513378e-175</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>chr3_132093815_132106295</td>\n",
       "      <td>5.072335</td>\n",
       "      <td>9.590057e-65</td>\n",
       "      <td>6.924867e-62</td>\n",
       "      <td>Dkk2</td>\n",
       "      <td>-6.916087</td>\n",
       "      <td>9.389039e-178</td>\n",
       "      <td>5.513378e-175</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>chr3_141699368_141702608</td>\n",
       "      <td>6.065565</td>\n",
       "      <td>2.403341e-29</td>\n",
       "      <td>5.413249e-27</td>\n",
       "      <td>Bmpr1b</td>\n",
       "      <td>-5.570116</td>\n",
       "      <td>6.893076e-40</td>\n",
       "      <td>3.655998e-38</td>\n",
       "      <td>134528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>chr4_68535893_68538867</td>\n",
       "      <td>5.172571</td>\n",
       "      <td>1.974087e-15</td>\n",
       "      <td>1.648497e-13</td>\n",
       "      <td>Brinp1</td>\n",
       "      <td>-7.758307</td>\n",
       "      <td>5.384595e-10</td>\n",
       "      <td>5.726618e-09</td>\n",
       "      <td>222505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>chr4_68545353_68551019</td>\n",
       "      <td>6.825275</td>\n",
       "      <td>1.516093e-18</td>\n",
       "      <td>1.684235e-16</td>\n",
       "      <td>Brinp1</td>\n",
       "      <td>-7.758307</td>\n",
       "      <td>5.384595e-10</td>\n",
       "      <td>5.726618e-09</td>\n",
       "      <td>210353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>chr4_118022206_118024522</td>\n",
       "      <td>-5.332271</td>\n",
       "      <td>1.094775e-06</td>\n",
       "      <td>2.210347e-05</td>\n",
       "      <td>Artn</td>\n",
       "      <td>9.083650</td>\n",
       "      <td>8.043160e-84</td>\n",
       "      <td>1.066497e-81</td>\n",
       "      <td>-92444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>chr5_13001869_13003460</td>\n",
       "      <td>5.957213</td>\n",
       "      <td>2.037009e-10</td>\n",
       "      <td>8.898685e-09</td>\n",
       "      <td>Sema3a</td>\n",
       "      <td>-5.771471</td>\n",
       "      <td>3.017136e-297</td>\n",
       "      <td>6.200968e-294</td>\n",
       "      <td>393324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>chr5_13276479_13283560</td>\n",
       "      <td>7.727895</td>\n",
       "      <td>3.536779e-34</td>\n",
       "      <td>1.033708e-31</td>\n",
       "      <td>Sema3a</td>\n",
       "      <td>-5.771471</td>\n",
       "      <td>3.017136e-297</td>\n",
       "      <td>6.200968e-294</td>\n",
       "      <td>113224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>chr5_17080302_17082934</td>\n",
       "      <td>5.024623</td>\n",
       "      <td>9.959617e-06</td>\n",
       "      <td>1.561421e-04</td>\n",
       "      <td>Hgf</td>\n",
       "      <td>-7.513756</td>\n",
       "      <td>2.543270e-09</td>\n",
       "      <td>2.523623e-08</td>\n",
       "      <td>-460864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>chr5_28465271_28467276</td>\n",
       "      <td>-5.397757</td>\n",
       "      <td>5.546104e-07</td>\n",
       "      <td>1.202787e-05</td>\n",
       "      <td>Shh</td>\n",
       "      <td>5.565109</td>\n",
       "      <td>2.158809e-156</td>\n",
       "      <td>9.593279e-154</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>chr5_38081825_38086331</td>\n",
       "      <td>6.088429</td>\n",
       "      <td>2.350343e-11</td>\n",
       "      <td>1.192216e-09</td>\n",
       "      <td>Nsg1</td>\n",
       "      <td>-5.086635</td>\n",
       "      <td>2.233941e-111</td>\n",
       "      <td>4.963574e-109</td>\n",
       "      <td>50862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>chr7_56523378_56528436</td>\n",
       "      <td>6.721266</td>\n",
       "      <td>2.699280e-17</td>\n",
       "      <td>2.609056e-15</td>\n",
       "      <td>Gabrg3</td>\n",
       "      <td>-5.960560</td>\n",
       "      <td>2.341610e-05</td>\n",
       "      <td>1.323050e-04</td>\n",
       "      <td>195806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>chr7_111875691_111878313</td>\n",
       "      <td>5.109476</td>\n",
       "      <td>4.848742e-06</td>\n",
       "      <td>8.221096e-05</td>\n",
       "      <td>Galnt18</td>\n",
       "      <td>-5.959958</td>\n",
       "      <td>2.253335e-68</td>\n",
       "      <td>2.218523e-66</td>\n",
       "      <td>-95715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>chr8_82329336_82331284</td>\n",
       "      <td>5.189615</td>\n",
       "      <td>2.360560e-06</td>\n",
       "      <td>4.324934e-05</td>\n",
       "      <td>Il15</td>\n",
       "      <td>-5.185933</td>\n",
       "      <td>8.096707e-04</td>\n",
       "      <td>3.267016e-03</td>\n",
       "      <td>340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>chr8_102781569_102784308</td>\n",
       "      <td>5.761340</td>\n",
       "      <td>3.626346e-09</td>\n",
       "      <td>1.222945e-07</td>\n",
       "      <td>Cdh11</td>\n",
       "      <td>-6.729272</td>\n",
       "      <td>1.932941e-232</td>\n",
       "      <td>1.986339e-229</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>chr11_96341058_96343216</td>\n",
       "      <td>5.337659</td>\n",
       "      <td>5.594815e-07</td>\n",
       "      <td>1.202787e-05</td>\n",
       "      <td>Hoxb3</td>\n",
       "      <td>-6.433657</td>\n",
       "      <td>6.669080e-07</td>\n",
       "      <td>4.796719e-06</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>chr11_96354206_96355627</td>\n",
       "      <td>5.109476</td>\n",
       "      <td>4.848742e-06</td>\n",
       "      <td>8.221096e-05</td>\n",
       "      <td>Hoxb3</td>\n",
       "      <td>-6.433657</td>\n",
       "      <td>6.669080e-07</td>\n",
       "      <td>4.796719e-06</td>\n",
       "      <td>-6277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>chr11_96354206_96355627</td>\n",
       "      <td>5.109476</td>\n",
       "      <td>4.848742e-06</td>\n",
       "      <td>8.221096e-05</td>\n",
       "      <td>Hoxb2</td>\n",
       "      <td>-6.351656</td>\n",
       "      <td>3.359549e-06</td>\n",
       "      <td>2.173857e-05</td>\n",
       "      <td>-193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>chr12_56506841_56514912</td>\n",
       "      <td>-9.259195</td>\n",
       "      <td>2.083740e-95</td>\n",
       "      <td>3.009288e-92</td>\n",
       "      <td>Nkx2-1</td>\n",
       "      <td>9.134857</td>\n",
       "      <td>1.061953e-60</td>\n",
       "      <td>9.189803e-59</td>\n",
       "      <td>17023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>chr13_117409406_117414817</td>\n",
       "      <td>-5.127606</td>\n",
       "      <td>3.397970e-15</td>\n",
       "      <td>2.771547e-13</td>\n",
       "      <td>Emb</td>\n",
       "      <td>-6.021510</td>\n",
       "      <td>3.917980e-06</td>\n",
       "      <td>2.506593e-05</td>\n",
       "      <td>-134992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>chr14_66104432_66107303</td>\n",
       "      <td>6.455571</td>\n",
       "      <td>1.757505e-14</td>\n",
       "      <td>1.344190e-12</td>\n",
       "      <td>Ephx2</td>\n",
       "      <td>-6.872942</td>\n",
       "      <td>1.597944e-07</td>\n",
       "      <td>1.247549e-06</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>chr14_88460573_88463273</td>\n",
       "      <td>5.594736</td>\n",
       "      <td>3.142836e-08</td>\n",
       "      <td>8.899628e-07</td>\n",
       "      <td>Pcdh20</td>\n",
       "      <td>-6.097424</td>\n",
       "      <td>1.179837e-05</td>\n",
       "      <td>6.988068e-05</td>\n",
       "      <td>1474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>chr14_88898125_88900211</td>\n",
       "      <td>-5.263671</td>\n",
       "      <td>2.162151e-06</td>\n",
       "      <td>4.039800e-05</td>\n",
       "      <td>Pcdh20</td>\n",
       "      <td>-6.097424</td>\n",
       "      <td>1.179837e-05</td>\n",
       "      <td>6.988068e-05</td>\n",
       "      <td>-426730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>chr15_11692586_11694713</td>\n",
       "      <td>6.046002</td>\n",
       "      <td>4.827833e-11</td>\n",
       "      <td>2.333231e-09</td>\n",
       "      <td>Npr3</td>\n",
       "      <td>-8.356128</td>\n",
       "      <td>2.957230e-242</td>\n",
       "      <td>3.473055e-239</td>\n",
       "      <td>145183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>chr15_11743634_11745456</td>\n",
       "      <td>6.922288</td>\n",
       "      <td>8.515240e-20</td>\n",
       "      <td>1.034939e-17</td>\n",
       "      <td>Npr3</td>\n",
       "      <td>-8.356128</td>\n",
       "      <td>2.957230e-242</td>\n",
       "      <td>3.473055e-239</td>\n",
       "      <td>94440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>chr15_11782997_11784930</td>\n",
       "      <td>5.957213</td>\n",
       "      <td>2.037009e-10</td>\n",
       "      <td>8.898685e-09</td>\n",
       "      <td>Npr3</td>\n",
       "      <td>-8.356128</td>\n",
       "      <td>2.957230e-242</td>\n",
       "      <td>3.473055e-239</td>\n",
       "      <td>54966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>chr18_53465649_53470088</td>\n",
       "      <td>5.761340</td>\n",
       "      <td>3.626346e-09</td>\n",
       "      <td>1.222945e-07</td>\n",
       "      <td>Prdm6</td>\n",
       "      <td>-9.029699</td>\n",
       "      <td>4.482978e-14</td>\n",
       "      <td>6.960257e-13</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>chr19_59159949_59161669</td>\n",
       "      <td>-6.094880</td>\n",
       "      <td>4.260481e-11</td>\n",
       "      <td>2.067175e-09</td>\n",
       "      <td>Vax1</td>\n",
       "      <td>7.636277</td>\n",
       "      <td>8.070915e-31</td>\n",
       "      <td>3.071805e-29</td>\n",
       "      <td>2816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>chr19_59163812_59165938</td>\n",
       "      <td>-5.788022</td>\n",
       "      <td>4.812885e-09</td>\n",
       "      <td>1.603272e-07</td>\n",
       "      <td>Vax1</td>\n",
       "      <td>7.636277</td>\n",
       "      <td>8.070915e-31</td>\n",
       "      <td>3.071805e-29</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>chrX_93281556_93288401</td>\n",
       "      <td>5.093695</td>\n",
       "      <td>9.655833e-32</td>\n",
       "      <td>2.469379e-29</td>\n",
       "      <td>Arx</td>\n",
       "      <td>-5.380834</td>\n",
       "      <td>6.537245e-123</td>\n",
       "      <td>1.853196e-120</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>chrY_1009018_1011799</td>\n",
       "      <td>-5.686862</td>\n",
       "      <td>1.864054e-08</td>\n",
       "      <td>5.507147e-07</td>\n",
       "      <td>Eif2s3y</td>\n",
       "      <td>11.645099</td>\n",
       "      <td>9.414457e-23</td>\n",
       "      <td>2.468780e-21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>chrY_1243715_1246316</td>\n",
       "      <td>-5.520433</td>\n",
       "      <td>1.425488e-07</td>\n",
       "      <td>3.468498e-06</td>\n",
       "      <td>Ddx3y</td>\n",
       "      <td>11.525927</td>\n",
       "      <td>2.291430e-22</td>\n",
       "      <td>5.823136e-21</td>\n",
       "      <td>14399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>chrY_1243715_1246316</td>\n",
       "      <td>-5.520433</td>\n",
       "      <td>1.425488e-07</td>\n",
       "      <td>3.468498e-06</td>\n",
       "      <td>Uty</td>\n",
       "      <td>8.369064</td>\n",
       "      <td>1.224906e-22</td>\n",
       "      <td>3.191744e-21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>chrY_1282482_1287504</td>\n",
       "      <td>-5.191646</td>\n",
       "      <td>4.272455e-06</td>\n",
       "      <td>7.350598e-05</td>\n",
       "      <td>Ddx3y</td>\n",
       "      <td>11.525927</td>\n",
       "      <td>2.291430e-22</td>\n",
       "      <td>5.823136e-21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Peak  logfoldchanges_peak    Pvalue_peak  \\\n",
       "0    chr1_174659622_174662521             5.652435   1.530047e-08   \n",
       "1    chr1_174917639_174921559             6.208699   2.711848e-12   \n",
       "2      chr2_93645657_93648162             5.189615   2.360560e-06   \n",
       "3      chr3_33140350_33142508             5.534632   6.455627e-08   \n",
       "4    chr3_126498429_126499612             5.337659   5.594815e-07   \n",
       "5    chr3_126657669_126660188            -5.397757   5.546104e-07   \n",
       "6    chr3_132085669_132092999             6.121213  1.509244e-105   \n",
       "7    chr3_132093815_132106295             5.072335   9.590057e-65   \n",
       "8    chr3_141699368_141702608             6.065565   2.403341e-29   \n",
       "9      chr4_68535893_68538867             5.172571   1.974087e-15   \n",
       "10     chr4_68545353_68551019             6.825275   1.516093e-18   \n",
       "11   chr4_118022206_118024522            -5.332271   1.094775e-06   \n",
       "12     chr5_13001869_13003460             5.957213   2.037009e-10   \n",
       "13     chr5_13276479_13283560             7.727895   3.536779e-34   \n",
       "14     chr5_17080302_17082934             5.024623   9.959617e-06   \n",
       "15     chr5_28465271_28467276            -5.397757   5.546104e-07   \n",
       "16     chr5_38081825_38086331             6.088429   2.350343e-11   \n",
       "17     chr7_56523378_56528436             6.721266   2.699280e-17   \n",
       "18   chr7_111875691_111878313             5.109476   4.848742e-06   \n",
       "19     chr8_82329336_82331284             5.189615   2.360560e-06   \n",
       "20   chr8_102781569_102784308             5.761340   3.626346e-09   \n",
       "21    chr11_96341058_96343216             5.337659   5.594815e-07   \n",
       "22    chr11_96354206_96355627             5.109476   4.848742e-06   \n",
       "23    chr11_96354206_96355627             5.109476   4.848742e-06   \n",
       "24    chr12_56506841_56514912            -9.259195   2.083740e-95   \n",
       "25  chr13_117409406_117414817            -5.127606   3.397970e-15   \n",
       "26    chr14_66104432_66107303             6.455571   1.757505e-14   \n",
       "27    chr14_88460573_88463273             5.594736   3.142836e-08   \n",
       "28    chr14_88898125_88900211            -5.263671   2.162151e-06   \n",
       "29    chr15_11692586_11694713             6.046002   4.827833e-11   \n",
       "30    chr15_11743634_11745456             6.922288   8.515240e-20   \n",
       "31    chr15_11782997_11784930             5.957213   2.037009e-10   \n",
       "32    chr18_53465649_53470088             5.761340   3.626346e-09   \n",
       "33    chr19_59159949_59161669            -6.094880   4.260481e-11   \n",
       "34    chr19_59163812_59165938            -5.788022   4.812885e-09   \n",
       "35     chrX_93281556_93288401             5.093695   9.655833e-32   \n",
       "36       chrY_1009018_1011799            -5.686862   1.864054e-08   \n",
       "37       chrY_1243715_1246316            -5.520433   1.425488e-07   \n",
       "38       chrY_1243715_1246316            -5.520433   1.425488e-07   \n",
       "39       chrY_1282482_1287504            -5.191646   4.272455e-06   \n",
       "\n",
       "    Pvalue_adj_peak     Gene  Score_gene    Pvalue_gene  Pvalue_adj_gene  \\\n",
       "0      4.586591e-07    Grem2  -10.401831   1.280025e-67     1.252748e-65   \n",
       "1      1.562878e-10    Grem2  -10.401831   1.280025e-67     1.252748e-65   \n",
       "2      4.324934e-05     Alx4  -10.292504   5.458739e-18     1.081356e-16   \n",
       "3      1.724615e-06    Pex5l   -7.590236   2.351122e-24     6.841972e-23   \n",
       "4      1.202787e-05     Arsj   -6.281259   8.667831e-27     2.783525e-25   \n",
       "5      1.202787e-05     Arsj   -6.281259   8.667831e-27     2.783525e-25   \n",
       "6     2.850264e-102     Dkk2   -6.916087  9.389039e-178    5.513378e-175   \n",
       "7      6.924867e-62     Dkk2   -6.916087  9.389039e-178    5.513378e-175   \n",
       "8      5.413249e-27   Bmpr1b   -5.570116   6.893076e-40     3.655998e-38   \n",
       "9      1.648497e-13   Brinp1   -7.758307   5.384595e-10     5.726618e-09   \n",
       "10     1.684235e-16   Brinp1   -7.758307   5.384595e-10     5.726618e-09   \n",
       "11     2.210347e-05     Artn    9.083650   8.043160e-84     1.066497e-81   \n",
       "12     8.898685e-09   Sema3a   -5.771471  3.017136e-297    6.200968e-294   \n",
       "13     1.033708e-31   Sema3a   -5.771471  3.017136e-297    6.200968e-294   \n",
       "14     1.561421e-04      Hgf   -7.513756   2.543270e-09     2.523623e-08   \n",
       "15     1.202787e-05      Shh    5.565109  2.158809e-156    9.593279e-154   \n",
       "16     1.192216e-09     Nsg1   -5.086635  2.233941e-111    4.963574e-109   \n",
       "17     2.609056e-15   Gabrg3   -5.960560   2.341610e-05     1.323050e-04   \n",
       "18     8.221096e-05  Galnt18   -5.959958   2.253335e-68     2.218523e-66   \n",
       "19     4.324934e-05     Il15   -5.185933   8.096707e-04     3.267016e-03   \n",
       "20     1.222945e-07    Cdh11   -6.729272  1.932941e-232    1.986339e-229   \n",
       "21     1.202787e-05    Hoxb3   -6.433657   6.669080e-07     4.796719e-06   \n",
       "22     8.221096e-05    Hoxb3   -6.433657   6.669080e-07     4.796719e-06   \n",
       "23     8.221096e-05    Hoxb2   -6.351656   3.359549e-06     2.173857e-05   \n",
       "24     3.009288e-92   Nkx2-1    9.134857   1.061953e-60     9.189803e-59   \n",
       "25     2.771547e-13      Emb   -6.021510   3.917980e-06     2.506593e-05   \n",
       "26     1.344190e-12    Ephx2   -6.872942   1.597944e-07     1.247549e-06   \n",
       "27     8.899628e-07   Pcdh20   -6.097424   1.179837e-05     6.988068e-05   \n",
       "28     4.039800e-05   Pcdh20   -6.097424   1.179837e-05     6.988068e-05   \n",
       "29     2.333231e-09     Npr3   -8.356128  2.957230e-242    3.473055e-239   \n",
       "30     1.034939e-17     Npr3   -8.356128  2.957230e-242    3.473055e-239   \n",
       "31     8.898685e-09     Npr3   -8.356128  2.957230e-242    3.473055e-239   \n",
       "32     1.222945e-07    Prdm6   -9.029699   4.482978e-14     6.960257e-13   \n",
       "33     2.067175e-09     Vax1    7.636277   8.070915e-31     3.071805e-29   \n",
       "34     1.603272e-07     Vax1    7.636277   8.070915e-31     3.071805e-29   \n",
       "35     2.469379e-29      Arx   -5.380834  6.537245e-123    1.853196e-120   \n",
       "36     5.507147e-07  Eif2s3y   11.645099   9.414457e-23     2.468780e-21   \n",
       "37     3.468498e-06    Ddx3y   11.525927   2.291430e-22     5.823136e-21   \n",
       "38     3.468498e-06      Uty    8.369064   1.224906e-22     3.191744e-21   \n",
       "39     7.350598e-05    Ddx3y   11.525927   2.291430e-22     5.823136e-21   \n",
       "\n",
       "    Distance_peak_to_gene  \n",
       "0                  171264  \n",
       "1                       0  \n",
       "2                       0  \n",
       "3                       0  \n",
       "4                  -58056  \n",
       "5                 -217296  \n",
       "6                       0  \n",
       "7                       0  \n",
       "8                  134528  \n",
       "9                  222505  \n",
       "10                 210353  \n",
       "11                 -92444  \n",
       "12                 393324  \n",
       "13                 113224  \n",
       "14                -460864  \n",
       "15                      0  \n",
       "16                  50862  \n",
       "17                 195806  \n",
       "18                 -95715  \n",
       "19                    340  \n",
       "20                      0  \n",
       "21                      0  \n",
       "22                  -6277  \n",
       "23                   -193  \n",
       "24                  17023  \n",
       "25                -134992  \n",
       "26                      0  \n",
       "27                   1474  \n",
       "28                -426730  \n",
       "29                 145183  \n",
       "30                  94440  \n",
       "31                  54966  \n",
       "32                      0  \n",
       "33                   2816  \n",
       "34                      0  \n",
       "35                      0  \n",
       "36                      0  \n",
       "37                  14399  \n",
       "38                      0  \n",
       "39                      0  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = cc.tl.pair_peak_gene_bulk(adata_cc, \"https://github.com/The-Mitra-Lab/pycallingcards_data/releases/download/data/deseq_MF.csv\", \n",
    "                                   name_cc = 'logfoldchanges', pvalue_cutoff_cc = 0.001, pvalue_cutoff_rna = 0.001, \n",
    "                                   lfc_cutoff_rna = 5, lfc_cutoff_cc = 5)\n",
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63ba816b-29ef-4fb2-be2a-77209ea73031",
   "metadata": {},
   "source": [
    "Next, we visualize, for specific peaks, the magnitude of differential binding and the expression of nearby genes using the dotplot function.  This function creates a dotplot with three columns (below).  The first shows the relative binding of Brd4 at a chromsomal locus in males and females, the second and third columns show the expression levels of the nearest and second nearest genes in males and females. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "b7519eab-2662-424d-8b75-030c47bbab91",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x1600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cc.pl.dotplot_bulk(adata_cc, rna, selected_list = list(np.unique(np.array(result[\"Peak\"]))), num_list = [3,3], dotsize = 500,\n",
    "                   cmap = 'plasma', figsize = (16, 16), sort_by_chrom = True, topspace = 0.96)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b203480-c4f9-4f65-b248-e8cf3d7e8ab3",
   "metadata": {},
   "source": [
    "We can see from these results that all of the peaks visualized here display differential binding, and either the nearest, or second nearest gene has differential expression. In most cases, increased Brd4 binding is associated with an increase in gene expression. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9921875-057c-4ef0-b642-836028129094",
   "metadata": {},
   "source": [
    "Pycallingcards provides functionality to explore relatinoships between differentially bound regions and nearby GWAS identified SNPs. Since the data analyzed here were collected in murine cells, we must first lift over any interesting peaks to the human genome before we can look for nearby disease associated SNPs. We use [liftover](https://genome.ucsc.edu/cgi-bin/hgLiftOver) to get the resuls."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "93b7d8c3-21d7-439c-b68c-7a83ff38371e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Start mapping the peaks to the new genome.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 40/40 [00:00<00:00, 69.43it/s] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Start finding location of genes in the new genome.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 40/40 [00:00<00:00, 287.78it/s]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Peak</th>\n",
       "      <th>logfoldchanges_peak</th>\n",
       "      <th>Pvalue_peak</th>\n",
       "      <th>Pvalue_adj_peak</th>\n",
       "      <th>Gene</th>\n",
       "      <th>Score_gene</th>\n",
       "      <th>Pvalue_gene</th>\n",
       "      <th>Pvalue_adj_gene</th>\n",
       "      <th>Distance_peak_to_gene</th>\n",
       "      <th>Chr_liftover</th>\n",
       "      <th>Start_liftover</th>\n",
       "      <th>End_liftover</th>\n",
       "      <th>Chr_hg38</th>\n",
       "      <th>Start_hg38</th>\n",
       "      <th>End_hg38</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1_174659622_174662521</td>\n",
       "      <td>5.652435</td>\n",
       "      <td>1.530047e-08</td>\n",
       "      <td>4.586591e-07</td>\n",
       "      <td>Grem2</td>\n",
       "      <td>-10.401831</td>\n",
       "      <td>1.280025e-67</td>\n",
       "      <td>1.252748e-65</td>\n",
       "      <td>171264</td>\n",
       "      <td>chr1</td>\n",
       "      <td>240280756</td>\n",
       "      <td>240283835</td>\n",
       "      <td>chr1</td>\n",
       "      <td>240489572</td>\n",
       "      <td>240612162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1_174917639_174921559</td>\n",
       "      <td>6.208699</td>\n",
       "      <td>2.711848e-12</td>\n",
       "      <td>1.562878e-10</td>\n",
       "      <td>Grem2</td>\n",
       "      <td>-10.401831</td>\n",
       "      <td>1.280025e-67</td>\n",
       "      <td>1.252748e-65</td>\n",
       "      <td>0</td>\n",
       "      <td>chr1</td>\n",
       "      <td>240608636</td>\n",
       "      <td>240611870</td>\n",
       "      <td>chr1</td>\n",
       "      <td>240489572</td>\n",
       "      <td>240612162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr2_93645657_93648162</td>\n",
       "      <td>5.189615</td>\n",
       "      <td>2.360560e-06</td>\n",
       "      <td>4.324934e-05</td>\n",
       "      <td>Alx4</td>\n",
       "      <td>-10.292504</td>\n",
       "      <td>5.458739e-18</td>\n",
       "      <td>1.081356e-16</td>\n",
       "      <td>0</td>\n",
       "      <td>chr11</td>\n",
       "      <td>44303696</td>\n",
       "      <td>44306415</td>\n",
       "      <td>chr11</td>\n",
       "      <td>44260727</td>\n",
       "      <td>44310166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr3_33140350_33142508</td>\n",
       "      <td>5.534632</td>\n",
       "      <td>6.455627e-08</td>\n",
       "      <td>1.724615e-06</td>\n",
       "      <td>Pex5l</td>\n",
       "      <td>-7.590236</td>\n",
       "      <td>2.351122e-24</td>\n",
       "      <td>6.841972e-23</td>\n",
       "      <td>0</td>\n",
       "      <td>chr3</td>\n",
       "      <td>180033883</td>\n",
       "      <td>180036186</td>\n",
       "      <td>chr3</td>\n",
       "      <td>179794958</td>\n",
       "      <td>180037053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr3_126498429_126499612</td>\n",
       "      <td>5.337659</td>\n",
       "      <td>5.594815e-07</td>\n",
       "      <td>1.202787e-05</td>\n",
       "      <td>Arsj</td>\n",
       "      <td>-6.281259</td>\n",
       "      <td>8.667831e-27</td>\n",
       "      <td>2.783525e-25</td>\n",
       "      <td>-58056</td>\n",
       "      <td>chr4</td>\n",
       "      <td>113839066</td>\n",
       "      <td>113844568</td>\n",
       "      <td>chr4</td>\n",
       "      <td>113900283</td>\n",
       "      <td>113979722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>chr3_126657669_126660188</td>\n",
       "      <td>-5.397757</td>\n",
       "      <td>5.546104e-07</td>\n",
       "      <td>1.202787e-05</td>\n",
       "      <td>Arsj</td>\n",
       "      <td>-6.281259</td>\n",
       "      <td>8.667831e-27</td>\n",
       "      <td>2.783525e-25</td>\n",
       "      <td>-217296</td>\n",
       "      <td>chr4</td>\n",
       "      <td>113683844</td>\n",
       "      <td>113686758</td>\n",
       "      <td>chr4</td>\n",
       "      <td>113900283</td>\n",
       "      <td>113979722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>chr3_132085669_132092999</td>\n",
       "      <td>6.121213</td>\n",
       "      <td>1.509244e-105</td>\n",
       "      <td>2.850264e-102</td>\n",
       "      <td>Dkk2</td>\n",
       "      <td>-6.916087</td>\n",
       "      <td>9.389039e-178</td>\n",
       "      <td>5.513378e-175</td>\n",
       "      <td>0</td>\n",
       "      <td>chr4</td>\n",
       "      <td>107029387</td>\n",
       "      <td>107035946</td>\n",
       "      <td>chr4</td>\n",
       "      <td>106921801</td>\n",
       "      <td>107036296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>chr3_132093815_132106295</td>\n",
       "      <td>5.072335</td>\n",
       "      <td>9.590057e-65</td>\n",
       "      <td>6.924867e-62</td>\n",
       "      <td>Dkk2</td>\n",
       "      <td>-6.916087</td>\n",
       "      <td>9.389039e-178</td>\n",
       "      <td>5.513378e-175</td>\n",
       "      <td>0</td>\n",
       "      <td>chr4</td>\n",
       "      <td>107015456</td>\n",
       "      <td>107028826</td>\n",
       "      <td>chr4</td>\n",
       "      <td>106921801</td>\n",
       "      <td>107036296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>chr3_141699368_141702608</td>\n",
       "      <td>6.065565</td>\n",
       "      <td>2.403341e-29</td>\n",
       "      <td>5.413249e-27</td>\n",
       "      <td>Bmpr1b</td>\n",
       "      <td>-5.570116</td>\n",
       "      <td>6.893076e-40</td>\n",
       "      <td>3.655998e-38</td>\n",
       "      <td>134528</td>\n",
       "      <td>chr4</td>\n",
       "      <td>95306647</td>\n",
       "      <td>95309431</td>\n",
       "      <td>chr4</td>\n",
       "      <td>94757976</td>\n",
       "      <td>95158450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>chr4_68535893_68538867</td>\n",
       "      <td>5.172571</td>\n",
       "      <td>1.974087e-15</td>\n",
       "      <td>1.648497e-13</td>\n",
       "      <td>Brinp1</td>\n",
       "      <td>-7.758307</td>\n",
       "      <td>5.384595e-10</td>\n",
       "      <td>5.726618e-09</td>\n",
       "      <td>222505</td>\n",
       "      <td>chr9</td>\n",
       "      <td>118993297</td>\n",
       "      <td>118996641</td>\n",
       "      <td>chr9</td>\n",
       "      <td>119166629</td>\n",
       "      <td>119369461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>chr4_68545353_68551019</td>\n",
       "      <td>6.825275</td>\n",
       "      <td>1.516093e-18</td>\n",
       "      <td>1.684235e-16</td>\n",
       "      <td>Brinp1</td>\n",
       "      <td>-7.758307</td>\n",
       "      <td>5.384595e-10</td>\n",
       "      <td>5.726618e-09</td>\n",
       "      <td>210353</td>\n",
       "      <td>chr9</td>\n",
       "      <td>119002823</td>\n",
       "      <td>119008509</td>\n",
       "      <td>chr9</td>\n",
       "      <td>119166629</td>\n",
       "      <td>119369461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>chr4_118022206_118024522</td>\n",
       "      <td>-5.332271</td>\n",
       "      <td>1.094775e-06</td>\n",
       "      <td>2.210347e-05</td>\n",
       "      <td>Artn</td>\n",
       "      <td>9.083650</td>\n",
       "      <td>8.043160e-84</td>\n",
       "      <td>1.066497e-81</td>\n",
       "      <td>-92444</td>\n",
       "      <td>chr1</td>\n",
       "      <td>43824383</td>\n",
       "      <td>43825212</td>\n",
       "      <td>chr1</td>\n",
       "      <td>43933319</td>\n",
       "      <td>43937240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>chr5_13001869_13003460</td>\n",
       "      <td>5.957213</td>\n",
       "      <td>2.037009e-10</td>\n",
       "      <td>8.898685e-09</td>\n",
       "      <td>Sema3a</td>\n",
       "      <td>-5.771471</td>\n",
       "      <td>3.017136e-297</td>\n",
       "      <td>6.200968e-294</td>\n",
       "      <td>393324</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>chr7</td>\n",
       "      <td>83958342</td>\n",
       "      <td>84194901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>chr5_13276479_13283560</td>\n",
       "      <td>7.727895</td>\n",
       "      <td>3.536779e-34</td>\n",
       "      <td>1.033708e-31</td>\n",
       "      <td>Sema3a</td>\n",
       "      <td>-5.771471</td>\n",
       "      <td>3.017136e-297</td>\n",
       "      <td>6.200968e-294</td>\n",
       "      <td>113224</td>\n",
       "      <td>chr7</td>\n",
       "      <td>84314176</td>\n",
       "      <td>84318280</td>\n",
       "      <td>chr7</td>\n",
       "      <td>83958342</td>\n",
       "      <td>84194901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>chr5_17080302_17082934</td>\n",
       "      <td>5.024623</td>\n",
       "      <td>9.959617e-06</td>\n",
       "      <td>1.561421e-04</td>\n",
       "      <td>Hgf</td>\n",
       "      <td>-7.513756</td>\n",
       "      <td>2.543270e-09</td>\n",
       "      <td>2.523623e-08</td>\n",
       "      <td>-460864</td>\n",
       "      <td>chr7</td>\n",
       "      <td>81335127</td>\n",
       "      <td>81335733</td>\n",
       "      <td>chr7</td>\n",
       "      <td>81699007</td>\n",
       "      <td>81770198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>chr5_28465271_28467276</td>\n",
       "      <td>-5.397757</td>\n",
       "      <td>5.546104e-07</td>\n",
       "      <td>1.202787e-05</td>\n",
       "      <td>Shh</td>\n",
       "      <td>5.565109</td>\n",
       "      <td>2.158809e-156</td>\n",
       "      <td>9.593279e-154</td>\n",
       "      <td>0</td>\n",
       "      <td>chr7</td>\n",
       "      <td>155810616</td>\n",
       "      <td>155812624</td>\n",
       "      <td>chr7</td>\n",
       "      <td>155799983</td>\n",
       "      <td>155812273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>chr5_38081825_38086331</td>\n",
       "      <td>6.088429</td>\n",
       "      <td>2.350343e-11</td>\n",
       "      <td>1.192216e-09</td>\n",
       "      <td>Nsg1</td>\n",
       "      <td>-5.086635</td>\n",
       "      <td>2.233941e-111</td>\n",
       "      <td>4.963574e-109</td>\n",
       "      <td>50862</td>\n",
       "      <td>chr4</td>\n",
       "      <td>4488485</td>\n",
       "      <td>4493470</td>\n",
       "      <td>chr4</td>\n",
       "      <td>4386255</td>\n",
       "      <td>4419058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>chr7_56523378_56528436</td>\n",
       "      <td>6.721266</td>\n",
       "      <td>2.699280e-17</td>\n",
       "      <td>2.609056e-15</td>\n",
       "      <td>Gabrg3</td>\n",
       "      <td>-5.960560</td>\n",
       "      <td>2.341610e-05</td>\n",
       "      <td>1.323050e-04</td>\n",
       "      <td>195806</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>chr15</td>\n",
       "      <td>26971281</td>\n",
       "      <td>27533227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>chr7_111875691_111878313</td>\n",
       "      <td>5.109476</td>\n",
       "      <td>4.848742e-06</td>\n",
       "      <td>8.221096e-05</td>\n",
       "      <td>Galnt18</td>\n",
       "      <td>-5.959958</td>\n",
       "      <td>2.253335e-68</td>\n",
       "      <td>2.218523e-66</td>\n",
       "      <td>-95715</td>\n",
       "      <td>chr11</td>\n",
       "      <td>11723801</td>\n",
       "      <td>11725419</td>\n",
       "      <td>chr11</td>\n",
       "      <td>11270873</td>\n",
       "      <td>11622014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>chr8_82329336_82331284</td>\n",
       "      <td>5.189615</td>\n",
       "      <td>2.360560e-06</td>\n",
       "      <td>4.324934e-05</td>\n",
       "      <td>Il15</td>\n",
       "      <td>-5.185933</td>\n",
       "      <td>8.096707e-04</td>\n",
       "      <td>3.267016e-03</td>\n",
       "      <td>340</td>\n",
       "      <td>chr4</td>\n",
       "      <td>141733679</td>\n",
       "      <td>141736013</td>\n",
       "      <td>chr4</td>\n",
       "      <td>141636595</td>\n",
       "      <td>141733987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>chr8_102781569_102784308</td>\n",
       "      <td>5.761340</td>\n",
       "      <td>3.626346e-09</td>\n",
       "      <td>1.222945e-07</td>\n",
       "      <td>Cdh11</td>\n",
       "      <td>-6.729272</td>\n",
       "      <td>1.932941e-232</td>\n",
       "      <td>1.986339e-229</td>\n",
       "      <td>0</td>\n",
       "      <td>chr16</td>\n",
       "      <td>65118621</td>\n",
       "      <td>65121296</td>\n",
       "      <td>chr16</td>\n",
       "      <td>64943752</td>\n",
       "      <td>65122137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>chr11_96341058_96343216</td>\n",
       "      <td>5.337659</td>\n",
       "      <td>5.594815e-07</td>\n",
       "      <td>1.202787e-05</td>\n",
       "      <td>Hoxb3</td>\n",
       "      <td>-6.433657</td>\n",
       "      <td>6.669080e-07</td>\n",
       "      <td>4.796719e-06</td>\n",
       "      <td>0</td>\n",
       "      <td>chr17</td>\n",
       "      <td>48553538</td>\n",
       "      <td>48555622</td>\n",
       "      <td>chr17</td>\n",
       "      <td>48548869</td>\n",
       "      <td>48582622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>chr11_96354206_96355627</td>\n",
       "      <td>5.109476</td>\n",
       "      <td>4.848742e-06</td>\n",
       "      <td>8.221096e-05</td>\n",
       "      <td>Hoxb3</td>\n",
       "      <td>-6.433657</td>\n",
       "      <td>6.669080e-07</td>\n",
       "      <td>4.796719e-06</td>\n",
       "      <td>-6277</td>\n",
       "      <td>chr17</td>\n",
       "      <td>48540790</td>\n",
       "      <td>48542479</td>\n",
       "      <td>chr17</td>\n",
       "      <td>48548869</td>\n",
       "      <td>48582622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>chr11_96354206_96355627</td>\n",
       "      <td>5.109476</td>\n",
       "      <td>4.848742e-06</td>\n",
       "      <td>8.221096e-05</td>\n",
       "      <td>Hoxb2</td>\n",
       "      <td>-6.351656</td>\n",
       "      <td>3.359549e-06</td>\n",
       "      <td>2.173857e-05</td>\n",
       "      <td>-193</td>\n",
       "      <td>chr17</td>\n",
       "      <td>48540790</td>\n",
       "      <td>48542479</td>\n",
       "      <td>chr17</td>\n",
       "      <td>48542655</td>\n",
       "      <td>48545031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>chr12_56506841_56514912</td>\n",
       "      <td>-9.259195</td>\n",
       "      <td>2.083740e-95</td>\n",
       "      <td>3.009288e-92</td>\n",
       "      <td>Nkx2-1</td>\n",
       "      <td>9.134857</td>\n",
       "      <td>1.061953e-60</td>\n",
       "      <td>9.189803e-59</td>\n",
       "      <td>17023</td>\n",
       "      <td>chr14</td>\n",
       "      <td>36491565</td>\n",
       "      <td>36499712</td>\n",
       "      <td>chr14</td>\n",
       "      <td>36516398</td>\n",
       "      <td>36520225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>chr13_117409406_117414817</td>\n",
       "      <td>-5.127606</td>\n",
       "      <td>3.397970e-15</td>\n",
       "      <td>2.771547e-13</td>\n",
       "      <td>Emb</td>\n",
       "      <td>-6.021510</td>\n",
       "      <td>3.917980e-06</td>\n",
       "      <td>2.506593e-05</td>\n",
       "      <td>-134992</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>chr5</td>\n",
       "      <td>50396196</td>\n",
       "      <td>50441400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>chr14_66104432_66107303</td>\n",
       "      <td>6.455571</td>\n",
       "      <td>1.757505e-14</td>\n",
       "      <td>1.344190e-12</td>\n",
       "      <td>Ephx2</td>\n",
       "      <td>-6.872942</td>\n",
       "      <td>1.597944e-07</td>\n",
       "      <td>1.247549e-06</td>\n",
       "      <td>0</td>\n",
       "      <td>chr8</td>\n",
       "      <td>27506903</td>\n",
       "      <td>27511135</td>\n",
       "      <td>chr8</td>\n",
       "      <td>27491001</td>\n",
       "      <td>27544922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>chr14_88460573_88463273</td>\n",
       "      <td>5.594736</td>\n",
       "      <td>3.142836e-08</td>\n",
       "      <td>8.899628e-07</td>\n",
       "      <td>Pcdh20</td>\n",
       "      <td>-6.097424</td>\n",
       "      <td>1.179837e-05</td>\n",
       "      <td>6.988068e-05</td>\n",
       "      <td>1474</td>\n",
       "      <td>chr13</td>\n",
       "      <td>61406547</td>\n",
       "      <td>61407676</td>\n",
       "      <td>chr13</td>\n",
       "      <td>61409685</td>\n",
       "      <td>61415522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>chr14_88898125_88900211</td>\n",
       "      <td>-5.263671</td>\n",
       "      <td>2.162151e-06</td>\n",
       "      <td>4.039800e-05</td>\n",
       "      <td>Pcdh20</td>\n",
       "      <td>-6.097424</td>\n",
       "      <td>1.179837e-05</td>\n",
       "      <td>6.988068e-05</td>\n",
       "      <td>-426730</td>\n",
       "      <td>chr13</td>\n",
       "      <td>61862674</td>\n",
       "      <td>61862983</td>\n",
       "      <td>chr13</td>\n",
       "      <td>61409685</td>\n",
       "      <td>61415522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>chr15_11692586_11694713</td>\n",
       "      <td>6.046002</td>\n",
       "      <td>4.827833e-11</td>\n",
       "      <td>2.333231e-09</td>\n",
       "      <td>Npr3</td>\n",
       "      <td>-8.356128</td>\n",
       "      <td>2.957230e-242</td>\n",
       "      <td>3.473055e-239</td>\n",
       "      <td>145183</td>\n",
       "      <td>chr5</td>\n",
       "      <td>33023231</td>\n",
       "      <td>33024567</td>\n",
       "      <td>chr5</td>\n",
       "      <td>32710636</td>\n",
       "      <td>32791724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>chr15_11743634_11745456</td>\n",
       "      <td>6.922288</td>\n",
       "      <td>8.515240e-20</td>\n",
       "      <td>1.034939e-17</td>\n",
       "      <td>Npr3</td>\n",
       "      <td>-8.356128</td>\n",
       "      <td>2.957230e-242</td>\n",
       "      <td>3.473055e-239</td>\n",
       "      <td>94440</td>\n",
       "      <td>chr5</td>\n",
       "      <td>32929090</td>\n",
       "      <td>32932829</td>\n",
       "      <td>chr5</td>\n",
       "      <td>32710636</td>\n",
       "      <td>32791724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>chr15_11782997_11784930</td>\n",
       "      <td>5.957213</td>\n",
       "      <td>2.037009e-10</td>\n",
       "      <td>8.898685e-09</td>\n",
       "      <td>Npr3</td>\n",
       "      <td>-8.356128</td>\n",
       "      <td>2.957230e-242</td>\n",
       "      <td>3.473055e-239</td>\n",
       "      <td>54966</td>\n",
       "      <td>chr5</td>\n",
       "      <td>32864592</td>\n",
       "      <td>32866245</td>\n",
       "      <td>chr5</td>\n",
       "      <td>32710636</td>\n",
       "      <td>32791724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>chr18_53465649_53470088</td>\n",
       "      <td>5.761340</td>\n",
       "      <td>3.626346e-09</td>\n",
       "      <td>1.222945e-07</td>\n",
       "      <td>Prdm6</td>\n",
       "      <td>-9.029699</td>\n",
       "      <td>4.482978e-14</td>\n",
       "      <td>6.960257e-13</td>\n",
       "      <td>0</td>\n",
       "      <td>chr5</td>\n",
       "      <td>123091173</td>\n",
       "      <td>123096087</td>\n",
       "      <td>chr5</td>\n",
       "      <td>123089102</td>\n",
       "      <td>123194266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>chr19_59159949_59161669</td>\n",
       "      <td>-6.094880</td>\n",
       "      <td>4.260481e-11</td>\n",
       "      <td>2.067175e-09</td>\n",
       "      <td>Vax1</td>\n",
       "      <td>7.636277</td>\n",
       "      <td>8.070915e-31</td>\n",
       "      <td>3.071805e-29</td>\n",
       "      <td>2816</td>\n",
       "      <td>chr10</td>\n",
       "      <td>117127894</td>\n",
       "      <td>117129270</td>\n",
       "      <td>chr10</td>\n",
       "      <td>117128520</td>\n",
       "      <td>117138301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>chr19_59163812_59165938</td>\n",
       "      <td>-5.788022</td>\n",
       "      <td>4.812885e-09</td>\n",
       "      <td>1.603272e-07</td>\n",
       "      <td>Vax1</td>\n",
       "      <td>7.636277</td>\n",
       "      <td>8.070915e-31</td>\n",
       "      <td>3.071805e-29</td>\n",
       "      <td>0</td>\n",
       "      <td>chr10</td>\n",
       "      <td>117131583</td>\n",
       "      <td>117133776</td>\n",
       "      <td>chr10</td>\n",
       "      <td>117128520</td>\n",
       "      <td>117138301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>chrX_93281556_93288401</td>\n",
       "      <td>5.093695</td>\n",
       "      <td>9.655833e-32</td>\n",
       "      <td>2.469379e-29</td>\n",
       "      <td>Arx</td>\n",
       "      <td>-5.380834</td>\n",
       "      <td>6.537245e-123</td>\n",
       "      <td>1.853196e-120</td>\n",
       "      <td>0</td>\n",
       "      <td>chrX</td>\n",
       "      <td>25013967</td>\n",
       "      <td>25020980</td>\n",
       "      <td>chrX</td>\n",
       "      <td>25003695</td>\n",
       "      <td>25015948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>chrY_1009018_1011799</td>\n",
       "      <td>-5.686862</td>\n",
       "      <td>1.864054e-08</td>\n",
       "      <td>5.507147e-07</td>\n",
       "      <td>Eif2s3y</td>\n",
       "      <td>11.645099</td>\n",
       "      <td>9.414457e-23</td>\n",
       "      <td>2.468780e-21</td>\n",
       "      <td>0</td>\n",
       "      <td>chrX</td>\n",
       "      <td>24054686</td>\n",
       "      <td>24057370</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>chrY_1243715_1246316</td>\n",
       "      <td>-5.520433</td>\n",
       "      <td>1.425488e-07</td>\n",
       "      <td>3.468498e-06</td>\n",
       "      <td>Ddx3y</td>\n",
       "      <td>11.525927</td>\n",
       "      <td>2.291430e-22</td>\n",
       "      <td>5.823136e-21</td>\n",
       "      <td>14399</td>\n",
       "      <td>chrY</td>\n",
       "      <td>13478375</td>\n",
       "      <td>13480067</td>\n",
       "      <td>chrY</td>\n",
       "      <td>12903998</td>\n",
       "      <td>12920478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>chrY_1243715_1246316</td>\n",
       "      <td>-5.520433</td>\n",
       "      <td>1.425488e-07</td>\n",
       "      <td>3.468498e-06</td>\n",
       "      <td>Uty</td>\n",
       "      <td>8.369064</td>\n",
       "      <td>1.224906e-22</td>\n",
       "      <td>3.191744e-21</td>\n",
       "      <td>0</td>\n",
       "      <td>chrY</td>\n",
       "      <td>13478375</td>\n",
       "      <td>13480067</td>\n",
       "      <td>chrY</td>\n",
       "      <td>13248378</td>\n",
       "      <td>13480670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>chrY_1282482_1287504</td>\n",
       "      <td>-5.191646</td>\n",
       "      <td>4.272455e-06</td>\n",
       "      <td>7.350598e-05</td>\n",
       "      <td>Ddx3y</td>\n",
       "      <td>11.525927</td>\n",
       "      <td>2.291430e-22</td>\n",
       "      <td>5.823136e-21</td>\n",
       "      <td>0</td>\n",
       "      <td>chrY</td>\n",
       "      <td>12903183</td>\n",
       "      <td>12909538</td>\n",
       "      <td>chrY</td>\n",
       "      <td>12903998</td>\n",
       "      <td>12920478</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Peak  logfoldchanges_peak    Pvalue_peak  \\\n",
       "0    chr1_174659622_174662521             5.652435   1.530047e-08   \n",
       "1    chr1_174917639_174921559             6.208699   2.711848e-12   \n",
       "2      chr2_93645657_93648162             5.189615   2.360560e-06   \n",
       "3      chr3_33140350_33142508             5.534632   6.455627e-08   \n",
       "4    chr3_126498429_126499612             5.337659   5.594815e-07   \n",
       "5    chr3_126657669_126660188            -5.397757   5.546104e-07   \n",
       "6    chr3_132085669_132092999             6.121213  1.509244e-105   \n",
       "7    chr3_132093815_132106295             5.072335   9.590057e-65   \n",
       "8    chr3_141699368_141702608             6.065565   2.403341e-29   \n",
       "9      chr4_68535893_68538867             5.172571   1.974087e-15   \n",
       "10     chr4_68545353_68551019             6.825275   1.516093e-18   \n",
       "11   chr4_118022206_118024522            -5.332271   1.094775e-06   \n",
       "12     chr5_13001869_13003460             5.957213   2.037009e-10   \n",
       "13     chr5_13276479_13283560             7.727895   3.536779e-34   \n",
       "14     chr5_17080302_17082934             5.024623   9.959617e-06   \n",
       "15     chr5_28465271_28467276            -5.397757   5.546104e-07   \n",
       "16     chr5_38081825_38086331             6.088429   2.350343e-11   \n",
       "17     chr7_56523378_56528436             6.721266   2.699280e-17   \n",
       "18   chr7_111875691_111878313             5.109476   4.848742e-06   \n",
       "19     chr8_82329336_82331284             5.189615   2.360560e-06   \n",
       "20   chr8_102781569_102784308             5.761340   3.626346e-09   \n",
       "21    chr11_96341058_96343216             5.337659   5.594815e-07   \n",
       "22    chr11_96354206_96355627             5.109476   4.848742e-06   \n",
       "23    chr11_96354206_96355627             5.109476   4.848742e-06   \n",
       "24    chr12_56506841_56514912            -9.259195   2.083740e-95   \n",
       "25  chr13_117409406_117414817            -5.127606   3.397970e-15   \n",
       "26    chr14_66104432_66107303             6.455571   1.757505e-14   \n",
       "27    chr14_88460573_88463273             5.594736   3.142836e-08   \n",
       "28    chr14_88898125_88900211            -5.263671   2.162151e-06   \n",
       "29    chr15_11692586_11694713             6.046002   4.827833e-11   \n",
       "30    chr15_11743634_11745456             6.922288   8.515240e-20   \n",
       "31    chr15_11782997_11784930             5.957213   2.037009e-10   \n",
       "32    chr18_53465649_53470088             5.761340   3.626346e-09   \n",
       "33    chr19_59159949_59161669            -6.094880   4.260481e-11   \n",
       "34    chr19_59163812_59165938            -5.788022   4.812885e-09   \n",
       "35     chrX_93281556_93288401             5.093695   9.655833e-32   \n",
       "36       chrY_1009018_1011799            -5.686862   1.864054e-08   \n",
       "37       chrY_1243715_1246316            -5.520433   1.425488e-07   \n",
       "38       chrY_1243715_1246316            -5.520433   1.425488e-07   \n",
       "39       chrY_1282482_1287504            -5.191646   4.272455e-06   \n",
       "\n",
       "    Pvalue_adj_peak     Gene  Score_gene    Pvalue_gene  Pvalue_adj_gene  \\\n",
       "0      4.586591e-07    Grem2  -10.401831   1.280025e-67     1.252748e-65   \n",
       "1      1.562878e-10    Grem2  -10.401831   1.280025e-67     1.252748e-65   \n",
       "2      4.324934e-05     Alx4  -10.292504   5.458739e-18     1.081356e-16   \n",
       "3      1.724615e-06    Pex5l   -7.590236   2.351122e-24     6.841972e-23   \n",
       "4      1.202787e-05     Arsj   -6.281259   8.667831e-27     2.783525e-25   \n",
       "5      1.202787e-05     Arsj   -6.281259   8.667831e-27     2.783525e-25   \n",
       "6     2.850264e-102     Dkk2   -6.916087  9.389039e-178    5.513378e-175   \n",
       "7      6.924867e-62     Dkk2   -6.916087  9.389039e-178    5.513378e-175   \n",
       "8      5.413249e-27   Bmpr1b   -5.570116   6.893076e-40     3.655998e-38   \n",
       "9      1.648497e-13   Brinp1   -7.758307   5.384595e-10     5.726618e-09   \n",
       "10     1.684235e-16   Brinp1   -7.758307   5.384595e-10     5.726618e-09   \n",
       "11     2.210347e-05     Artn    9.083650   8.043160e-84     1.066497e-81   \n",
       "12     8.898685e-09   Sema3a   -5.771471  3.017136e-297    6.200968e-294   \n",
       "13     1.033708e-31   Sema3a   -5.771471  3.017136e-297    6.200968e-294   \n",
       "14     1.561421e-04      Hgf   -7.513756   2.543270e-09     2.523623e-08   \n",
       "15     1.202787e-05      Shh    5.565109  2.158809e-156    9.593279e-154   \n",
       "16     1.192216e-09     Nsg1   -5.086635  2.233941e-111    4.963574e-109   \n",
       "17     2.609056e-15   Gabrg3   -5.960560   2.341610e-05     1.323050e-04   \n",
       "18     8.221096e-05  Galnt18   -5.959958   2.253335e-68     2.218523e-66   \n",
       "19     4.324934e-05     Il15   -5.185933   8.096707e-04     3.267016e-03   \n",
       "20     1.222945e-07    Cdh11   -6.729272  1.932941e-232    1.986339e-229   \n",
       "21     1.202787e-05    Hoxb3   -6.433657   6.669080e-07     4.796719e-06   \n",
       "22     8.221096e-05    Hoxb3   -6.433657   6.669080e-07     4.796719e-06   \n",
       "23     8.221096e-05    Hoxb2   -6.351656   3.359549e-06     2.173857e-05   \n",
       "24     3.009288e-92   Nkx2-1    9.134857   1.061953e-60     9.189803e-59   \n",
       "25     2.771547e-13      Emb   -6.021510   3.917980e-06     2.506593e-05   \n",
       "26     1.344190e-12    Ephx2   -6.872942   1.597944e-07     1.247549e-06   \n",
       "27     8.899628e-07   Pcdh20   -6.097424   1.179837e-05     6.988068e-05   \n",
       "28     4.039800e-05   Pcdh20   -6.097424   1.179837e-05     6.988068e-05   \n",
       "29     2.333231e-09     Npr3   -8.356128  2.957230e-242    3.473055e-239   \n",
       "30     1.034939e-17     Npr3   -8.356128  2.957230e-242    3.473055e-239   \n",
       "31     8.898685e-09     Npr3   -8.356128  2.957230e-242    3.473055e-239   \n",
       "32     1.222945e-07    Prdm6   -9.029699   4.482978e-14     6.960257e-13   \n",
       "33     2.067175e-09     Vax1    7.636277   8.070915e-31     3.071805e-29   \n",
       "34     1.603272e-07     Vax1    7.636277   8.070915e-31     3.071805e-29   \n",
       "35     2.469379e-29      Arx   -5.380834  6.537245e-123    1.853196e-120   \n",
       "36     5.507147e-07  Eif2s3y   11.645099   9.414457e-23     2.468780e-21   \n",
       "37     3.468498e-06    Ddx3y   11.525927   2.291430e-22     5.823136e-21   \n",
       "38     3.468498e-06      Uty    8.369064   1.224906e-22     3.191744e-21   \n",
       "39     7.350598e-05    Ddx3y   11.525927   2.291430e-22     5.823136e-21   \n",
       "\n",
       "    Distance_peak_to_gene Chr_liftover Start_liftover End_liftover Chr_hg38  \\\n",
       "0                  171264         chr1      240280756    240283835     chr1   \n",
       "1                       0         chr1      240608636    240611870     chr1   \n",
       "2                       0        chr11       44303696     44306415    chr11   \n",
       "3                       0         chr3      180033883    180036186     chr3   \n",
       "4                  -58056         chr4      113839066    113844568     chr4   \n",
       "5                 -217296         chr4      113683844    113686758     chr4   \n",
       "6                       0         chr4      107029387    107035946     chr4   \n",
       "7                       0         chr4      107015456    107028826     chr4   \n",
       "8                  134528         chr4       95306647     95309431     chr4   \n",
       "9                  222505         chr9      118993297    118996641     chr9   \n",
       "10                 210353         chr9      119002823    119008509     chr9   \n",
       "11                 -92444         chr1       43824383     43825212     chr1   \n",
       "12                 393324                                              chr7   \n",
       "13                 113224         chr7       84314176     84318280     chr7   \n",
       "14                -460864         chr7       81335127     81335733     chr7   \n",
       "15                      0         chr7      155810616    155812624     chr7   \n",
       "16                  50862         chr4        4488485      4493470     chr4   \n",
       "17                 195806                                             chr15   \n",
       "18                 -95715        chr11       11723801     11725419    chr11   \n",
       "19                    340         chr4      141733679    141736013     chr4   \n",
       "20                      0        chr16       65118621     65121296    chr16   \n",
       "21                      0        chr17       48553538     48555622    chr17   \n",
       "22                  -6277        chr17       48540790     48542479    chr17   \n",
       "23                   -193        chr17       48540790     48542479    chr17   \n",
       "24                  17023        chr14       36491565     36499712    chr14   \n",
       "25                -134992                                              chr5   \n",
       "26                      0         chr8       27506903     27511135     chr8   \n",
       "27                   1474        chr13       61406547     61407676    chr13   \n",
       "28                -426730        chr13       61862674     61862983    chr13   \n",
       "29                 145183         chr5       33023231     33024567     chr5   \n",
       "30                  94440         chr5       32929090     32932829     chr5   \n",
       "31                  54966         chr5       32864592     32866245     chr5   \n",
       "32                      0         chr5      123091173    123096087     chr5   \n",
       "33                   2816        chr10      117127894    117129270    chr10   \n",
       "34                      0        chr10      117131583    117133776    chr10   \n",
       "35                      0         chrX       25013967     25020980     chrX   \n",
       "36                      0         chrX       24054686     24057370            \n",
       "37                  14399         chrY       13478375     13480067     chrY   \n",
       "38                      0         chrY       13478375     13480067     chrY   \n",
       "39                      0         chrY       12903183     12909538     chrY   \n",
       "\n",
       "   Start_hg38   End_hg38  \n",
       "0   240489572  240612162  \n",
       "1   240489572  240612162  \n",
       "2    44260727   44310166  \n",
       "3   179794958  180037053  \n",
       "4   113900283  113979722  \n",
       "5   113900283  113979722  \n",
       "6   106921801  107036296  \n",
       "7   106921801  107036296  \n",
       "8    94757976   95158450  \n",
       "9   119166629  119369461  \n",
       "10  119166629  119369461  \n",
       "11   43933319   43937240  \n",
       "12   83958342   84194901  \n",
       "13   83958342   84194901  \n",
       "14   81699007   81770198  \n",
       "15  155799983  155812273  \n",
       "16    4386255    4419058  \n",
       "17   26971281   27533227  \n",
       "18   11270873   11622014  \n",
       "19  141636595  141733987  \n",
       "20   64943752   65122137  \n",
       "21   48548869   48582622  \n",
       "22   48548869   48582622  \n",
       "23   48542655   48545031  \n",
       "24   36516398   36520225  \n",
       "25   50396196   50441400  \n",
       "26   27491001   27544922  \n",
       "27   61409685   61415522  \n",
       "28   61409685   61415522  \n",
       "29   32710636   32791724  \n",
       "30   32710636   32791724  \n",
       "31   32710636   32791724  \n",
       "32  123089102  123194266  \n",
       "33  117128520  117138301  \n",
       "34  117128520  117138301  \n",
       "35   25003695   25015948  \n",
       "36                        \n",
       "37   12903998   12920478  \n",
       "38   13248378   13480670  \n",
       "39   12903998   12920478  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = cc.tl.result_mapping(result)\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "2b255993-5681-4e84-bc5f-ae8d2fdd5264",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Peak</th>\n",
       "      <th>logfoldchanges_peak</th>\n",
       "      <th>Pvalue_peak</th>\n",
       "      <th>Pvalue_adj_peak</th>\n",
       "      <th>Gene</th>\n",
       "      <th>Score_gene</th>\n",
       "      <th>Pvalue_gene</th>\n",
       "      <th>Pvalue_adj_gene</th>\n",
       "      <th>Distance_peak_to_gene</th>\n",
       "      <th>Chr_liftover</th>\n",
       "      <th>Start_liftover</th>\n",
       "      <th>End_liftover</th>\n",
       "      <th>Chr_hg38</th>\n",
       "      <th>Start_hg38</th>\n",
       "      <th>End_hg38</th>\n",
       "      <th>GWAS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1_174659622_174662521</td>\n",
       "      <td>5.652435</td>\n",
       "      <td>1.530047e-08</td>\n",
       "      <td>4.586591e-07</td>\n",
       "      <td>Grem2</td>\n",
       "      <td>-10.401831</td>\n",
       "      <td>1.280025e-67</td>\n",
       "      <td>1.252748e-65</td>\n",
       "      <td>171264</td>\n",
       "      <td>chr1</td>\n",
       "      <td>240280756</td>\n",
       "      <td>240283835</td>\n",
       "      <td>chr1</td>\n",
       "      <td>240489572</td>\n",
       "      <td>240612162</td>\n",
       "      <td>Coronary heart disease</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1_174917639_174921559</td>\n",
       "      <td>6.208699</td>\n",
       "      <td>2.711848e-12</td>\n",
       "      <td>1.562878e-10</td>\n",
       "      <td>Grem2</td>\n",
       "      <td>-10.401831</td>\n",
       "      <td>1.280025e-67</td>\n",
       "      <td>1.252748e-65</td>\n",
       "      <td>0</td>\n",
       "      <td>chr1</td>\n",
       "      <td>240608636</td>\n",
       "      <td>240611870</td>\n",
       "      <td>chr1</td>\n",
       "      <td>240489572</td>\n",
       "      <td>240612162</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr2_93645657_93648162</td>\n",
       "      <td>5.189615</td>\n",
       "      <td>2.360560e-06</td>\n",
       "      <td>4.324934e-05</td>\n",
       "      <td>Alx4</td>\n",
       "      <td>-10.292504</td>\n",
       "      <td>5.458739e-18</td>\n",
       "      <td>1.081356e-16</td>\n",
       "      <td>0</td>\n",
       "      <td>chr11</td>\n",
       "      <td>44303696</td>\n",
       "      <td>44306415</td>\n",
       "      <td>chr11</td>\n",
       "      <td>44260727</td>\n",
       "      <td>44310166</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr3_33140350_33142508</td>\n",
       "      <td>5.534632</td>\n",
       "      <td>6.455627e-08</td>\n",
       "      <td>1.724615e-06</td>\n",
       "      <td>Pex5l</td>\n",
       "      <td>-7.590236</td>\n",
       "      <td>2.351122e-24</td>\n",
       "      <td>6.841972e-23</td>\n",
       "      <td>0</td>\n",
       "      <td>chr3</td>\n",
       "      <td>180033883</td>\n",
       "      <td>180036186</td>\n",
       "      <td>chr3</td>\n",
       "      <td>179794958</td>\n",
       "      <td>180037053</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr3_126498429_126499612</td>\n",
       "      <td>5.337659</td>\n",
       "      <td>5.594815e-07</td>\n",
       "      <td>1.202787e-05</td>\n",
       "      <td>Arsj</td>\n",
       "      <td>-6.281259</td>\n",
       "      <td>8.667831e-27</td>\n",
       "      <td>2.783525e-25</td>\n",
       "      <td>-58056</td>\n",
       "      <td>chr4</td>\n",
       "      <td>113839066</td>\n",
       "      <td>113844568</td>\n",
       "      <td>chr4</td>\n",
       "      <td>113900283</td>\n",
       "      <td>113979722</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>chr3_126657669_126660188</td>\n",
       "      <td>-5.397757</td>\n",
       "      <td>5.546104e-07</td>\n",
       "      <td>1.202787e-05</td>\n",
       "      <td>Arsj</td>\n",
       "      <td>-6.281259</td>\n",
       "      <td>8.667831e-27</td>\n",
       "      <td>2.783525e-25</td>\n",
       "      <td>-217296</td>\n",
       "      <td>chr4</td>\n",
       "      <td>113683844</td>\n",
       "      <td>113686758</td>\n",
       "      <td>chr4</td>\n",
       "      <td>113900283</td>\n",
       "      <td>113979722</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>chr3_132085669_132092999</td>\n",
       "      <td>6.121213</td>\n",
       "      <td>1.509244e-105</td>\n",
       "      <td>2.850264e-102</td>\n",
       "      <td>Dkk2</td>\n",
       "      <td>-6.916087</td>\n",
       "      <td>9.389039e-178</td>\n",
       "      <td>5.513378e-175</td>\n",
       "      <td>0</td>\n",
       "      <td>chr4</td>\n",
       "      <td>107029387</td>\n",
       "      <td>107035946</td>\n",
       "      <td>chr4</td>\n",
       "      <td>106921801</td>\n",
       "      <td>107036296</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>chr3_132093815_132106295</td>\n",
       "      <td>5.072335</td>\n",
       "      <td>9.590057e-65</td>\n",
       "      <td>6.924867e-62</td>\n",
       "      <td>Dkk2</td>\n",
       "      <td>-6.916087</td>\n",
       "      <td>9.389039e-178</td>\n",
       "      <td>5.513378e-175</td>\n",
       "      <td>0</td>\n",
       "      <td>chr4</td>\n",
       "      <td>107015456</td>\n",
       "      <td>107028826</td>\n",
       "      <td>chr4</td>\n",
       "      <td>106921801</td>\n",
       "      <td>107036296</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>chr3_141699368_141702608</td>\n",
       "      <td>6.065565</td>\n",
       "      <td>2.403341e-29</td>\n",
       "      <td>5.413249e-27</td>\n",
       "      <td>Bmpr1b</td>\n",
       "      <td>-5.570116</td>\n",
       "      <td>6.893076e-40</td>\n",
       "      <td>3.655998e-38</td>\n",
       "      <td>134528</td>\n",
       "      <td>chr4</td>\n",
       "      <td>95306647</td>\n",
       "      <td>95309431</td>\n",
       "      <td>chr4</td>\n",
       "      <td>94757976</td>\n",
       "      <td>95158450</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>chr4_68535893_68538867</td>\n",
       "      <td>5.172571</td>\n",
       "      <td>1.974087e-15</td>\n",
       "      <td>1.648497e-13</td>\n",
       "      <td>Brinp1</td>\n",
       "      <td>-7.758307</td>\n",
       "      <td>5.384595e-10</td>\n",
       "      <td>5.726618e-09</td>\n",
       "      <td>222505</td>\n",
       "      <td>chr9</td>\n",
       "      <td>118993297</td>\n",
       "      <td>118996641</td>\n",
       "      <td>chr9</td>\n",
       "      <td>119166629</td>\n",
       "      <td>119369461</td>\n",
       "      <td>Gut microbiota (bacterial taxa, hurdle binary ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>chr4_68545353_68551019</td>\n",
       "      <td>6.825275</td>\n",
       "      <td>1.516093e-18</td>\n",
       "      <td>1.684235e-16</td>\n",
       "      <td>Brinp1</td>\n",
       "      <td>-7.758307</td>\n",
       "      <td>5.384595e-10</td>\n",
       "      <td>5.726618e-09</td>\n",
       "      <td>210353</td>\n",
       "      <td>chr9</td>\n",
       "      <td>119002823</td>\n",
       "      <td>119008509</td>\n",
       "      <td>chr9</td>\n",
       "      <td>119166629</td>\n",
       "      <td>119369461</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>chr4_118022206_118024522</td>\n",
       "      <td>-5.332271</td>\n",
       "      <td>1.094775e-06</td>\n",
       "      <td>2.210347e-05</td>\n",
       "      <td>Artn</td>\n",
       "      <td>9.083650</td>\n",
       "      <td>8.043160e-84</td>\n",
       "      <td>1.066497e-81</td>\n",
       "      <td>-92444</td>\n",
       "      <td>chr1</td>\n",
       "      <td>43824383</td>\n",
       "      <td>43825212</td>\n",
       "      <td>chr1</td>\n",
       "      <td>43933319</td>\n",
       "      <td>43937240</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>chr5_13001869_13003460</td>\n",
       "      <td>5.957213</td>\n",
       "      <td>2.037009e-10</td>\n",
       "      <td>8.898685e-09</td>\n",
       "      <td>Sema3a</td>\n",
       "      <td>-5.771471</td>\n",
       "      <td>3.017136e-297</td>\n",
       "      <td>6.200968e-294</td>\n",
       "      <td>393324</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>chr7</td>\n",
       "      <td>83958342</td>\n",
       "      <td>84194901</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>chr5_13276479_13283560</td>\n",
       "      <td>7.727895</td>\n",
       "      <td>3.536779e-34</td>\n",
       "      <td>1.033708e-31</td>\n",
       "      <td>Sema3a</td>\n",
       "      <td>-5.771471</td>\n",
       "      <td>3.017136e-297</td>\n",
       "      <td>6.200968e-294</td>\n",
       "      <td>113224</td>\n",
       "      <td>chr7</td>\n",
       "      <td>84314176</td>\n",
       "      <td>84318280</td>\n",
       "      <td>chr7</td>\n",
       "      <td>83958342</td>\n",
       "      <td>84194901</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>chr5_17080302_17082934</td>\n",
       "      <td>5.024623</td>\n",
       "      <td>9.959617e-06</td>\n",
       "      <td>1.561421e-04</td>\n",
       "      <td>Hgf</td>\n",
       "      <td>-7.513756</td>\n",
       "      <td>2.543270e-09</td>\n",
       "      <td>2.523623e-08</td>\n",
       "      <td>-460864</td>\n",
       "      <td>chr7</td>\n",
       "      <td>81335127</td>\n",
       "      <td>81335733</td>\n",
       "      <td>chr7</td>\n",
       "      <td>81699007</td>\n",
       "      <td>81770198</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>chr5_28465271_28467276</td>\n",
       "      <td>-5.397757</td>\n",
       "      <td>5.546104e-07</td>\n",
       "      <td>1.202787e-05</td>\n",
       "      <td>Shh</td>\n",
       "      <td>5.565109</td>\n",
       "      <td>2.158809e-156</td>\n",
       "      <td>9.593279e-154</td>\n",
       "      <td>0</td>\n",
       "      <td>chr7</td>\n",
       "      <td>155810616</td>\n",
       "      <td>155812624</td>\n",
       "      <td>chr7</td>\n",
       "      <td>155799983</td>\n",
       "      <td>155812273</td>\n",
       "      <td>Urate levels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>chr5_38081825_38086331</td>\n",
       "      <td>6.088429</td>\n",
       "      <td>2.350343e-11</td>\n",
       "      <td>1.192216e-09</td>\n",
       "      <td>Nsg1</td>\n",
       "      <td>-5.086635</td>\n",
       "      <td>2.233941e-111</td>\n",
       "      <td>4.963574e-109</td>\n",
       "      <td>50862</td>\n",
       "      <td>chr4</td>\n",
       "      <td>4488485</td>\n",
       "      <td>4493470</td>\n",
       "      <td>chr4</td>\n",
       "      <td>4386255</td>\n",
       "      <td>4419058</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>chr7_56523378_56528436</td>\n",
       "      <td>6.721266</td>\n",
       "      <td>2.699280e-17</td>\n",
       "      <td>2.609056e-15</td>\n",
       "      <td>Gabrg3</td>\n",
       "      <td>-5.960560</td>\n",
       "      <td>2.341610e-05</td>\n",
       "      <td>1.323050e-04</td>\n",
       "      <td>195806</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>chr15</td>\n",
       "      <td>26971281</td>\n",
       "      <td>27533227</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>chr7_111875691_111878313</td>\n",
       "      <td>5.109476</td>\n",
       "      <td>4.848742e-06</td>\n",
       "      <td>8.221096e-05</td>\n",
       "      <td>Galnt18</td>\n",
       "      <td>-5.959958</td>\n",
       "      <td>2.253335e-68</td>\n",
       "      <td>2.218523e-66</td>\n",
       "      <td>-95715</td>\n",
       "      <td>chr11</td>\n",
       "      <td>11723801</td>\n",
       "      <td>11725419</td>\n",
       "      <td>chr11</td>\n",
       "      <td>11270873</td>\n",
       "      <td>11622014</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>chr8_82329336_82331284</td>\n",
       "      <td>5.189615</td>\n",
       "      <td>2.360560e-06</td>\n",
       "      <td>4.324934e-05</td>\n",
       "      <td>Il15</td>\n",
       "      <td>-5.185933</td>\n",
       "      <td>8.096707e-04</td>\n",
       "      <td>3.267016e-03</td>\n",
       "      <td>340</td>\n",
       "      <td>chr4</td>\n",
       "      <td>141733679</td>\n",
       "      <td>141736013</td>\n",
       "      <td>chr4</td>\n",
       "      <td>141636595</td>\n",
       "      <td>141733987</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>chr8_102781569_102784308</td>\n",
       "      <td>5.761340</td>\n",
       "      <td>3.626346e-09</td>\n",
       "      <td>1.222945e-07</td>\n",
       "      <td>Cdh11</td>\n",
       "      <td>-6.729272</td>\n",
       "      <td>1.932941e-232</td>\n",
       "      <td>1.986339e-229</td>\n",
       "      <td>0</td>\n",
       "      <td>chr16</td>\n",
       "      <td>65118621</td>\n",
       "      <td>65121296</td>\n",
       "      <td>chr16</td>\n",
       "      <td>64943752</td>\n",
       "      <td>65122137</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>chr11_96341058_96343216</td>\n",
       "      <td>5.337659</td>\n",
       "      <td>5.594815e-07</td>\n",
       "      <td>1.202787e-05</td>\n",
       "      <td>Hoxb3</td>\n",
       "      <td>-6.433657</td>\n",
       "      <td>6.669080e-07</td>\n",
       "      <td>4.796719e-06</td>\n",
       "      <td>0</td>\n",
       "      <td>chr17</td>\n",
       "      <td>48553538</td>\n",
       "      <td>48555622</td>\n",
       "      <td>chr17</td>\n",
       "      <td>48548869</td>\n",
       "      <td>48582622</td>\n",
       "      <td>Migraine; Insomnia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>chr11_96354206_96355627</td>\n",
       "      <td>5.109476</td>\n",
       "      <td>4.848742e-06</td>\n",
       "      <td>8.221096e-05</td>\n",
       "      <td>Hoxb3</td>\n",
       "      <td>-6.433657</td>\n",
       "      <td>6.669080e-07</td>\n",
       "      <td>4.796719e-06</td>\n",
       "      <td>-6277</td>\n",
       "      <td>chr17</td>\n",
       "      <td>48540790</td>\n",
       "      <td>48542479</td>\n",
       "      <td>chr17</td>\n",
       "      <td>48548869</td>\n",
       "      <td>48582622</td>\n",
       "      <td>Cystatin C levels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>chr11_96354206_96355627</td>\n",
       "      <td>5.109476</td>\n",
       "      <td>4.848742e-06</td>\n",
       "      <td>8.221096e-05</td>\n",
       "      <td>Hoxb2</td>\n",
       "      <td>-6.351656</td>\n",
       "      <td>3.359549e-06</td>\n",
       "      <td>2.173857e-05</td>\n",
       "      <td>-193</td>\n",
       "      <td>chr17</td>\n",
       "      <td>48540790</td>\n",
       "      <td>48542479</td>\n",
       "      <td>chr17</td>\n",
       "      <td>48542655</td>\n",
       "      <td>48545031</td>\n",
       "      <td>Cystatin C levels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>chr12_56506841_56514912</td>\n",
       "      <td>-9.259195</td>\n",
       "      <td>2.083740e-95</td>\n",
       "      <td>3.009288e-92</td>\n",
       "      <td>Nkx2-1</td>\n",
       "      <td>9.134857</td>\n",
       "      <td>1.061953e-60</td>\n",
       "      <td>9.189803e-59</td>\n",
       "      <td>17023</td>\n",
       "      <td>chr14</td>\n",
       "      <td>36491565</td>\n",
       "      <td>36499712</td>\n",
       "      <td>chr14</td>\n",
       "      <td>36516398</td>\n",
       "      <td>36520225</td>\n",
       "      <td>Nonsyndromic orofacial cleft x sex interaction...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>chr13_117409406_117414817</td>\n",
       "      <td>-5.127606</td>\n",
       "      <td>3.397970e-15</td>\n",
       "      <td>2.771547e-13</td>\n",
       "      <td>Emb</td>\n",
       "      <td>-6.021510</td>\n",
       "      <td>3.917980e-06</td>\n",
       "      <td>2.506593e-05</td>\n",
       "      <td>-134992</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>chr5</td>\n",
       "      <td>50396196</td>\n",
       "      <td>50441400</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>chr14_66104432_66107303</td>\n",
       "      <td>6.455571</td>\n",
       "      <td>1.757505e-14</td>\n",
       "      <td>1.344190e-12</td>\n",
       "      <td>Ephx2</td>\n",
       "      <td>-6.872942</td>\n",
       "      <td>1.597944e-07</td>\n",
       "      <td>1.247549e-06</td>\n",
       "      <td>0</td>\n",
       "      <td>chr8</td>\n",
       "      <td>27506903</td>\n",
       "      <td>27511135</td>\n",
       "      <td>chr8</td>\n",
       "      <td>27491001</td>\n",
       "      <td>27544922</td>\n",
       "      <td>Childhood ear infection</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>chr14_88460573_88463273</td>\n",
       "      <td>5.594736</td>\n",
       "      <td>3.142836e-08</td>\n",
       "      <td>8.899628e-07</td>\n",
       "      <td>Pcdh20</td>\n",
       "      <td>-6.097424</td>\n",
       "      <td>1.179837e-05</td>\n",
       "      <td>6.988068e-05</td>\n",
       "      <td>1474</td>\n",
       "      <td>chr13</td>\n",
       "      <td>61406547</td>\n",
       "      <td>61407676</td>\n",
       "      <td>chr13</td>\n",
       "      <td>61409685</td>\n",
       "      <td>61415522</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>chr14_88898125_88900211</td>\n",
       "      <td>-5.263671</td>\n",
       "      <td>2.162151e-06</td>\n",
       "      <td>4.039800e-05</td>\n",
       "      <td>Pcdh20</td>\n",
       "      <td>-6.097424</td>\n",
       "      <td>1.179837e-05</td>\n",
       "      <td>6.988068e-05</td>\n",
       "      <td>-426730</td>\n",
       "      <td>chr13</td>\n",
       "      <td>61862674</td>\n",
       "      <td>61862983</td>\n",
       "      <td>chr13</td>\n",
       "      <td>61409685</td>\n",
       "      <td>61415522</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>chr15_11692586_11694713</td>\n",
       "      <td>6.046002</td>\n",
       "      <td>4.827833e-11</td>\n",
       "      <td>2.333231e-09</td>\n",
       "      <td>Npr3</td>\n",
       "      <td>-8.356128</td>\n",
       "      <td>2.957230e-242</td>\n",
       "      <td>3.473055e-239</td>\n",
       "      <td>145183</td>\n",
       "      <td>chr5</td>\n",
       "      <td>33023231</td>\n",
       "      <td>33024567</td>\n",
       "      <td>chr5</td>\n",
       "      <td>32710636</td>\n",
       "      <td>32791724</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>chr15_11743634_11745456</td>\n",
       "      <td>6.922288</td>\n",
       "      <td>8.515240e-20</td>\n",
       "      <td>1.034939e-17</td>\n",
       "      <td>Npr3</td>\n",
       "      <td>-8.356128</td>\n",
       "      <td>2.957230e-242</td>\n",
       "      <td>3.473055e-239</td>\n",
       "      <td>94440</td>\n",
       "      <td>chr5</td>\n",
       "      <td>32929090</td>\n",
       "      <td>32932829</td>\n",
       "      <td>chr5</td>\n",
       "      <td>32710636</td>\n",
       "      <td>32791724</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>chr15_11782997_11784930</td>\n",
       "      <td>5.957213</td>\n",
       "      <td>2.037009e-10</td>\n",
       "      <td>8.898685e-09</td>\n",
       "      <td>Npr3</td>\n",
       "      <td>-8.356128</td>\n",
       "      <td>2.957230e-242</td>\n",
       "      <td>3.473055e-239</td>\n",
       "      <td>54966</td>\n",
       "      <td>chr5</td>\n",
       "      <td>32864592</td>\n",
       "      <td>32866245</td>\n",
       "      <td>chr5</td>\n",
       "      <td>32710636</td>\n",
       "      <td>32791724</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>chr18_53465649_53470088</td>\n",
       "      <td>5.761340</td>\n",
       "      <td>3.626346e-09</td>\n",
       "      <td>1.222945e-07</td>\n",
       "      <td>Prdm6</td>\n",
       "      <td>-9.029699</td>\n",
       "      <td>4.482978e-14</td>\n",
       "      <td>6.960257e-13</td>\n",
       "      <td>0</td>\n",
       "      <td>chr5</td>\n",
       "      <td>123091173</td>\n",
       "      <td>123096087</td>\n",
       "      <td>chr5</td>\n",
       "      <td>123089102</td>\n",
       "      <td>123194266</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>chr19_59159949_59161669</td>\n",
       "      <td>-6.094880</td>\n",
       "      <td>4.260481e-11</td>\n",
       "      <td>2.067175e-09</td>\n",
       "      <td>Vax1</td>\n",
       "      <td>7.636277</td>\n",
       "      <td>8.070915e-31</td>\n",
       "      <td>3.071805e-29</td>\n",
       "      <td>2816</td>\n",
       "      <td>chr10</td>\n",
       "      <td>117127894</td>\n",
       "      <td>117129270</td>\n",
       "      <td>chr10</td>\n",
       "      <td>117128520</td>\n",
       "      <td>117138301</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>chr19_59163812_59165938</td>\n",
       "      <td>-5.788022</td>\n",
       "      <td>4.812885e-09</td>\n",
       "      <td>1.603272e-07</td>\n",
       "      <td>Vax1</td>\n",
       "      <td>7.636277</td>\n",
       "      <td>8.070915e-31</td>\n",
       "      <td>3.071805e-29</td>\n",
       "      <td>0</td>\n",
       "      <td>chr10</td>\n",
       "      <td>117131583</td>\n",
       "      <td>117133776</td>\n",
       "      <td>chr10</td>\n",
       "      <td>117128520</td>\n",
       "      <td>117138301</td>\n",
       "      <td>Age at first birth; Nonsyndromic cleft lip wit...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>chrX_93281556_93288401</td>\n",
       "      <td>5.093695</td>\n",
       "      <td>9.655833e-32</td>\n",
       "      <td>2.469379e-29</td>\n",
       "      <td>Arx</td>\n",
       "      <td>-5.380834</td>\n",
       "      <td>6.537245e-123</td>\n",
       "      <td>1.853196e-120</td>\n",
       "      <td>0</td>\n",
       "      <td>chrX</td>\n",
       "      <td>25013967</td>\n",
       "      <td>25020980</td>\n",
       "      <td>chrX</td>\n",
       "      <td>25003695</td>\n",
       "      <td>25015948</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>chrY_1009018_1011799</td>\n",
       "      <td>-5.686862</td>\n",
       "      <td>1.864054e-08</td>\n",
       "      <td>5.507147e-07</td>\n",
       "      <td>Eif2s3y</td>\n",
       "      <td>11.645099</td>\n",
       "      <td>9.414457e-23</td>\n",
       "      <td>2.468780e-21</td>\n",
       "      <td>0</td>\n",
       "      <td>chrX</td>\n",
       "      <td>24054686</td>\n",
       "      <td>24057370</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>chrY_1243715_1246316</td>\n",
       "      <td>-5.520433</td>\n",
       "      <td>1.425488e-07</td>\n",
       "      <td>3.468498e-06</td>\n",
       "      <td>Ddx3y</td>\n",
       "      <td>11.525927</td>\n",
       "      <td>2.291430e-22</td>\n",
       "      <td>5.823136e-21</td>\n",
       "      <td>14399</td>\n",
       "      <td>chrY</td>\n",
       "      <td>13478375</td>\n",
       "      <td>13480067</td>\n",
       "      <td>chrY</td>\n",
       "      <td>12903998</td>\n",
       "      <td>12920478</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>chrY_1243715_1246316</td>\n",
       "      <td>-5.520433</td>\n",
       "      <td>1.425488e-07</td>\n",
       "      <td>3.468498e-06</td>\n",
       "      <td>Uty</td>\n",
       "      <td>8.369064</td>\n",
       "      <td>1.224906e-22</td>\n",
       "      <td>3.191744e-21</td>\n",
       "      <td>0</td>\n",
       "      <td>chrY</td>\n",
       "      <td>13478375</td>\n",
       "      <td>13480067</td>\n",
       "      <td>chrY</td>\n",
       "      <td>13248378</td>\n",
       "      <td>13480670</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>chrY_1282482_1287504</td>\n",
       "      <td>-5.191646</td>\n",
       "      <td>4.272455e-06</td>\n",
       "      <td>7.350598e-05</td>\n",
       "      <td>Ddx3y</td>\n",
       "      <td>11.525927</td>\n",
       "      <td>2.291430e-22</td>\n",
       "      <td>5.823136e-21</td>\n",
       "      <td>0</td>\n",
       "      <td>chrY</td>\n",
       "      <td>12903183</td>\n",
       "      <td>12909538</td>\n",
       "      <td>chrY</td>\n",
       "      <td>12903998</td>\n",
       "      <td>12920478</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Peak  logfoldchanges_peak    Pvalue_peak  \\\n",
       "0    chr1_174659622_174662521             5.652435   1.530047e-08   \n",
       "1    chr1_174917639_174921559             6.208699   2.711848e-12   \n",
       "2      chr2_93645657_93648162             5.189615   2.360560e-06   \n",
       "3      chr3_33140350_33142508             5.534632   6.455627e-08   \n",
       "4    chr3_126498429_126499612             5.337659   5.594815e-07   \n",
       "5    chr3_126657669_126660188            -5.397757   5.546104e-07   \n",
       "6    chr3_132085669_132092999             6.121213  1.509244e-105   \n",
       "7    chr3_132093815_132106295             5.072335   9.590057e-65   \n",
       "8    chr3_141699368_141702608             6.065565   2.403341e-29   \n",
       "9      chr4_68535893_68538867             5.172571   1.974087e-15   \n",
       "10     chr4_68545353_68551019             6.825275   1.516093e-18   \n",
       "11   chr4_118022206_118024522            -5.332271   1.094775e-06   \n",
       "12     chr5_13001869_13003460             5.957213   2.037009e-10   \n",
       "13     chr5_13276479_13283560             7.727895   3.536779e-34   \n",
       "14     chr5_17080302_17082934             5.024623   9.959617e-06   \n",
       "15     chr5_28465271_28467276            -5.397757   5.546104e-07   \n",
       "16     chr5_38081825_38086331             6.088429   2.350343e-11   \n",
       "17     chr7_56523378_56528436             6.721266   2.699280e-17   \n",
       "18   chr7_111875691_111878313             5.109476   4.848742e-06   \n",
       "19     chr8_82329336_82331284             5.189615   2.360560e-06   \n",
       "20   chr8_102781569_102784308             5.761340   3.626346e-09   \n",
       "21    chr11_96341058_96343216             5.337659   5.594815e-07   \n",
       "22    chr11_96354206_96355627             5.109476   4.848742e-06   \n",
       "23    chr11_96354206_96355627             5.109476   4.848742e-06   \n",
       "24    chr12_56506841_56514912            -9.259195   2.083740e-95   \n",
       "25  chr13_117409406_117414817            -5.127606   3.397970e-15   \n",
       "26    chr14_66104432_66107303             6.455571   1.757505e-14   \n",
       "27    chr14_88460573_88463273             5.594736   3.142836e-08   \n",
       "28    chr14_88898125_88900211            -5.263671   2.162151e-06   \n",
       "29    chr15_11692586_11694713             6.046002   4.827833e-11   \n",
       "30    chr15_11743634_11745456             6.922288   8.515240e-20   \n",
       "31    chr15_11782997_11784930             5.957213   2.037009e-10   \n",
       "32    chr18_53465649_53470088             5.761340   3.626346e-09   \n",
       "33    chr19_59159949_59161669            -6.094880   4.260481e-11   \n",
       "34    chr19_59163812_59165938            -5.788022   4.812885e-09   \n",
       "35     chrX_93281556_93288401             5.093695   9.655833e-32   \n",
       "36       chrY_1009018_1011799            -5.686862   1.864054e-08   \n",
       "37       chrY_1243715_1246316            -5.520433   1.425488e-07   \n",
       "38       chrY_1243715_1246316            -5.520433   1.425488e-07   \n",
       "39       chrY_1282482_1287504            -5.191646   4.272455e-06   \n",
       "\n",
       "    Pvalue_adj_peak     Gene  Score_gene    Pvalue_gene  Pvalue_adj_gene  \\\n",
       "0      4.586591e-07    Grem2  -10.401831   1.280025e-67     1.252748e-65   \n",
       "1      1.562878e-10    Grem2  -10.401831   1.280025e-67     1.252748e-65   \n",
       "2      4.324934e-05     Alx4  -10.292504   5.458739e-18     1.081356e-16   \n",
       "3      1.724615e-06    Pex5l   -7.590236   2.351122e-24     6.841972e-23   \n",
       "4      1.202787e-05     Arsj   -6.281259   8.667831e-27     2.783525e-25   \n",
       "5      1.202787e-05     Arsj   -6.281259   8.667831e-27     2.783525e-25   \n",
       "6     2.850264e-102     Dkk2   -6.916087  9.389039e-178    5.513378e-175   \n",
       "7      6.924867e-62     Dkk2   -6.916087  9.389039e-178    5.513378e-175   \n",
       "8      5.413249e-27   Bmpr1b   -5.570116   6.893076e-40     3.655998e-38   \n",
       "9      1.648497e-13   Brinp1   -7.758307   5.384595e-10     5.726618e-09   \n",
       "10     1.684235e-16   Brinp1   -7.758307   5.384595e-10     5.726618e-09   \n",
       "11     2.210347e-05     Artn    9.083650   8.043160e-84     1.066497e-81   \n",
       "12     8.898685e-09   Sema3a   -5.771471  3.017136e-297    6.200968e-294   \n",
       "13     1.033708e-31   Sema3a   -5.771471  3.017136e-297    6.200968e-294   \n",
       "14     1.561421e-04      Hgf   -7.513756   2.543270e-09     2.523623e-08   \n",
       "15     1.202787e-05      Shh    5.565109  2.158809e-156    9.593279e-154   \n",
       "16     1.192216e-09     Nsg1   -5.086635  2.233941e-111    4.963574e-109   \n",
       "17     2.609056e-15   Gabrg3   -5.960560   2.341610e-05     1.323050e-04   \n",
       "18     8.221096e-05  Galnt18   -5.959958   2.253335e-68     2.218523e-66   \n",
       "19     4.324934e-05     Il15   -5.185933   8.096707e-04     3.267016e-03   \n",
       "20     1.222945e-07    Cdh11   -6.729272  1.932941e-232    1.986339e-229   \n",
       "21     1.202787e-05    Hoxb3   -6.433657   6.669080e-07     4.796719e-06   \n",
       "22     8.221096e-05    Hoxb3   -6.433657   6.669080e-07     4.796719e-06   \n",
       "23     8.221096e-05    Hoxb2   -6.351656   3.359549e-06     2.173857e-05   \n",
       "24     3.009288e-92   Nkx2-1    9.134857   1.061953e-60     9.189803e-59   \n",
       "25     2.771547e-13      Emb   -6.021510   3.917980e-06     2.506593e-05   \n",
       "26     1.344190e-12    Ephx2   -6.872942   1.597944e-07     1.247549e-06   \n",
       "27     8.899628e-07   Pcdh20   -6.097424   1.179837e-05     6.988068e-05   \n",
       "28     4.039800e-05   Pcdh20   -6.097424   1.179837e-05     6.988068e-05   \n",
       "29     2.333231e-09     Npr3   -8.356128  2.957230e-242    3.473055e-239   \n",
       "30     1.034939e-17     Npr3   -8.356128  2.957230e-242    3.473055e-239   \n",
       "31     8.898685e-09     Npr3   -8.356128  2.957230e-242    3.473055e-239   \n",
       "32     1.222945e-07    Prdm6   -9.029699   4.482978e-14     6.960257e-13   \n",
       "33     2.067175e-09     Vax1    7.636277   8.070915e-31     3.071805e-29   \n",
       "34     1.603272e-07     Vax1    7.636277   8.070915e-31     3.071805e-29   \n",
       "35     2.469379e-29      Arx   -5.380834  6.537245e-123    1.853196e-120   \n",
       "36     5.507147e-07  Eif2s3y   11.645099   9.414457e-23     2.468780e-21   \n",
       "37     3.468498e-06    Ddx3y   11.525927   2.291430e-22     5.823136e-21   \n",
       "38     3.468498e-06      Uty    8.369064   1.224906e-22     3.191744e-21   \n",
       "39     7.350598e-05    Ddx3y   11.525927   2.291430e-22     5.823136e-21   \n",
       "\n",
       "    Distance_peak_to_gene Chr_liftover Start_liftover End_liftover Chr_hg38  \\\n",
       "0                  171264         chr1      240280756    240283835     chr1   \n",
       "1                       0         chr1      240608636    240611870     chr1   \n",
       "2                       0        chr11       44303696     44306415    chr11   \n",
       "3                       0         chr3      180033883    180036186     chr3   \n",
       "4                  -58056         chr4      113839066    113844568     chr4   \n",
       "5                 -217296         chr4      113683844    113686758     chr4   \n",
       "6                       0         chr4      107029387    107035946     chr4   \n",
       "7                       0         chr4      107015456    107028826     chr4   \n",
       "8                  134528         chr4       95306647     95309431     chr4   \n",
       "9                  222505         chr9      118993297    118996641     chr9   \n",
       "10                 210353         chr9      119002823    119008509     chr9   \n",
       "11                 -92444         chr1       43824383     43825212     chr1   \n",
       "12                 393324                                              chr7   \n",
       "13                 113224         chr7       84314176     84318280     chr7   \n",
       "14                -460864         chr7       81335127     81335733     chr7   \n",
       "15                      0         chr7      155810616    155812624     chr7   \n",
       "16                  50862         chr4        4488485      4493470     chr4   \n",
       "17                 195806                                             chr15   \n",
       "18                 -95715        chr11       11723801     11725419    chr11   \n",
       "19                    340         chr4      141733679    141736013     chr4   \n",
       "20                      0        chr16       65118621     65121296    chr16   \n",
       "21                      0        chr17       48553538     48555622    chr17   \n",
       "22                  -6277        chr17       48540790     48542479    chr17   \n",
       "23                   -193        chr17       48540790     48542479    chr17   \n",
       "24                  17023        chr14       36491565     36499712    chr14   \n",
       "25                -134992                                              chr5   \n",
       "26                      0         chr8       27506903     27511135     chr8   \n",
       "27                   1474        chr13       61406547     61407676    chr13   \n",
       "28                -426730        chr13       61862674     61862983    chr13   \n",
       "29                 145183         chr5       33023231     33024567     chr5   \n",
       "30                  94440         chr5       32929090     32932829     chr5   \n",
       "31                  54966         chr5       32864592     32866245     chr5   \n",
       "32                      0         chr5      123091173    123096087     chr5   \n",
       "33                   2816        chr10      117127894    117129270    chr10   \n",
       "34                      0        chr10      117131583    117133776    chr10   \n",
       "35                      0         chrX       25013967     25020980     chrX   \n",
       "36                      0         chrX       24054686     24057370            \n",
       "37                  14399         chrY       13478375     13480067     chrY   \n",
       "38                      0         chrY       13478375     13480067     chrY   \n",
       "39                      0         chrY       12903183     12909538     chrY   \n",
       "\n",
       "   Start_hg38   End_hg38                                               GWAS  \n",
       "0   240489572  240612162                             Coronary heart disease  \n",
       "1   240489572  240612162                                                     \n",
       "2    44260727   44310166                                                     \n",
       "3   179794958  180037053                                                     \n",
       "4   113900283  113979722                                                     \n",
       "5   113900283  113979722                                                     \n",
       "6   106921801  107036296                                                     \n",
       "7   106921801  107036296                                                     \n",
       "8    94757976   95158450                                                     \n",
       "9   119166629  119369461  Gut microbiota (bacterial taxa, hurdle binary ...  \n",
       "10  119166629  119369461                                                     \n",
       "11   43933319   43937240                                                     \n",
       "12   83958342   84194901                                                     \n",
       "13   83958342   84194901                                                     \n",
       "14   81699007   81770198                                                     \n",
       "15  155799983  155812273                                       Urate levels  \n",
       "16    4386255    4419058                                                     \n",
       "17   26971281   27533227                                                     \n",
       "18   11270873   11622014                                                     \n",
       "19  141636595  141733987                                                     \n",
       "20   64943752   65122137                                                     \n",
       "21   48548869   48582622                                 Migraine; Insomnia  \n",
       "22   48548869   48582622                                  Cystatin C levels  \n",
       "23   48542655   48545031                                  Cystatin C levels  \n",
       "24   36516398   36520225  Nonsyndromic orofacial cleft x sex interaction...  \n",
       "25   50396196   50441400                                                     \n",
       "26   27491001   27544922                            Childhood ear infection  \n",
       "27   61409685   61415522                                                     \n",
       "28   61409685   61415522                                                     \n",
       "29   32710636   32791724                                                     \n",
       "30   32710636   32791724                                                     \n",
       "31   32710636   32791724                                                     \n",
       "32  123089102  123194266                                                     \n",
       "33  117128520  117138301                                                     \n",
       "34  117128520  117138301  Age at first birth; Nonsyndromic cleft lip wit...  \n",
       "35   25003695   25015948                                                     \n",
       "36                                                                           \n",
       "37   12903998   12920478                                                     \n",
       "38   13248378   13480670                                                     \n",
       "39   12903998   12920478                                                     "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GWAS_result = cc.tl.GWAS(result)\n",
    "GWAS_result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9f62fb9-5fbc-4431-8f5e-7bebaa54af17",
   "metadata": {},
   "source": [
    "Save the file if needed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "a1e0d784-2be4-4692-afd5-18b800416fcd",
   "metadata": {},
   "outputs": [],
   "source": [
    "adata_cc.write(\"Brd4_bindings_bulk.h5ad\")"
   ]
  }
 ],
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