voyagerpy.utils.find_markers#

voyagerpy.utils.find_markers(adata: AnnData, hvg: bool = False, hvg_string: str = 'highly_variable', cluster: str = 'cluster') → dict#

Return summary statistics on differentially expressed genes by groups defined in cluster.

This function is based on findMarkers in scran.

Parameters:

  • adata (AnnData) – AnnData object with defined clustering in adata.obs.

  • hvg (bool, optional) – Whether to only test highly variable genes. The default is False.

  • hvg_string (str, optional) – String to identify highly variable genes in adata.var. The default is “highly_variable”.

  • cluster (str, optional) – String to identify cluster column in adata.obs. The default is “cluster”.

Returns:

Returns dictionary with summary statistics. P values, Benjamini-Hochberg False discovery rate, statistical measure of effect size, default for Mann-Whitney is AUC.

Return type:

dict