pilotpy.tl.gene_cluster_differentiation

pilotpy.tl.gene_cluster_differentiation(adata, cellnames=[], sort=['Expression pattern', 'adjusted P-value', 'R-squared'], number_genes=10, cluster_names=[], font_size=14, gene_list=[])

Perform gene cluster differentiation analysis.

Parameters

cellnameslist, optional

List of cell names for which you want to perform gene cluster differentiation analysis, by default [].

sortlist, optional

List of criteria for sorting gene expressions, by default [‘Expression pattern’, ‘adjusted P-value’, ‘R-squared’].

number_genesint, optional

Number of top genes to consider for each expression pattern, by default 10.

cluster_nameslist, optional

List of cluster names to consider for gene cluster differentiation, by default [].

font_sizeint, optional

Font size for plots, by default 12. gene_list=list, optional Your interested genes. If you have any intereted genes!

Returns

None. Performs gene cluster differentiation analysis based on specified parameters and saves the results.