SMURF

Import SMURF as:

import smurf as su

calculate_weight_to_celltype	Calculates the weight matrix mapping cell types to gene expression profiles.
expanding_cells	Expands cell regions by iteratively adding neighboring spots based on a scoring criterion.
get_finaldata	Combines cell and spot data after optimization to generate the final single-cell dataset.
get_finaldata_fast	Quickly generates the final single-cell dataset by combining cell and spot data without using GPU resources.
itering_arragement	Performs iterative cell arrangement for spatial transcriptomics analysis.
make_pixels_cells	Assigns cells to pixels in the spatial data based on spot compositions.
make_preparation	Prepares data for optimization by organizing cells and spots, calculating weights, and grouping cells for computational efficiency.
nuclei_rna	Creates an AnnData object for nuclei by aggregating spot-level gene expression data.
plot_cellcluster_position	Plots the spatial distribution of cell clusters and individual cell types.
plot_results	Plots the original tissue image with cell type assignments overlayed.
prepare_dataframe_image	Prepares the spatial data object by mapping tissue image data to spot positions.
return_celltype_plot	Generates a cell type assignment array based on clustering results for visualization.
singlecellanalysis	Performs standard single-cell RNA-seq analysis, including preprocessing, dimensionality reduction, clustering, and visualization.
start_optimization	Starts the optimization process to estimate cell-type proportions in each spot using PyTorch.