pycallingcards.tools.pair_peak_gene_sc_mu#

pycallingcards.tools.pair_peak_gene_sc_mu(mdata, adata_cc='CC', adata='RNA', peak_annotation=None, pvalue_adj_cutoff_cc=0.01, pvalue_adj_cutoff_rna=0.01, pvalue_cutoff_cc=None, pvalue_cutoff_rna=None, lfc_cutoff=3, score_cutoff=3, distance_cutoff=None, group_cc='binomtest', group_adata='rank_genes_groups', group_name='RNA:cluster', save_name='pair')[source]#

Pair related peaks and genes. Designed for mudata object. Find out significant binding peaks for one cluster and then see whether the annotated genes are also significantly expressed.

Parameters:

  • mdata (MuData) – mdata for both CC and RNA.

  • adata_cc (str (default: 'CC')) – Name for CC data. Anndata is mdata[adata_cc].

  • adata (str (default: 'RNA')) – Name for RNA data. Anndata is mdata[adata].

  • peak_annotation (Optional[DataFrame] (default: None)) – peak_annotation gotten from cc.pp.annotation and cc.pp.combine_annotation

  • pvalue_adj_cutoff_cc (Optional[float] (default: 0.01)) – The cut off value for the adjusted pvalues of adata_cc.

  • pvalue_adj_cutoff_rna (Optional[float] (default: 0.01)) – The cut off value for the adjusted pvalues of adata.

  • pvalue_cutoff_cc (Optional[float] (default: None)) – The cut off value for the pvalues of adata_cc.

  • pvalue_cutoff_rna (Optional[float] (default: None)) – The cut off value for the pvalues of adata.

  • lfc_cutoff (float (default: 3)) – The cut off value for the logfoldchange of adata_cc.

  • score_cutoff (float (default: 3)) – The cut off value for the cut of score value for adata.

  • distance_cutoff (Optional[float] (default: None)) – The cut off value for the cut of distance from peak to gene.

  • group_cc (str (default: 'binomtest')) – The name of target result in adata_cc.uns.

  • group_adata (str (default: 'rank_genes_groups')) – The name of target result in adata.uns.

  • group_name (str (default: 'RNA:cluster')) – The name of the cluster in mdata.obs.

  • save_name (str (default: 'pair')) – The name saved in mdata[adta_CC].uns.

Return type:

MuData

Example:

>>> import pycallingcards as cc
>>> mdata = cc.datasets.mousecortex_data(data="Mudata")
>>> cc.tl.pair_peak_gene_sc_mu(mdata, pvalue_cutoff_cc = 0.001, pvalue_cutoff_rna = 0.001, lfc_cutoff = 3, score_cutoff = 3)