simba.tl.find_master_regulators

simba.tl.find_master_regulators(adata_all, list_tf_motif=None, list_tf_gene=None, metric='euclidean', anno_filter='entity_anno', filter_gene='gene', metrics_gene=None, metrics_motif=None, cutoff_gene_max=1.5, cutoff_gene_gini=0.3, cutoff_gene_std=None, cutoff_gene_entropy=None, cutoff_motif_max=1.5, cutoff_motif_gini=0.3, cutoff_motif_std=None, cutoff_motif_entropy=None)[source]

Find all the master regulators

Parameters:

  • adata_all (AnnData) – Anndata object storing SIMBA embedding of all entities.

  • list_tf_motif (list) – A list of TF motifs. They should match TF motifs in list_tf_gene.

  • list_tf_gene (list) – A list TF genes. They should match TF motifs in list_tf_motif.

  • metric (str, optional (default: “euclidean”)) – The distance metric to use. It can be ‘braycurtis’, ‘canberra’, ‘chebyshev’, ‘cityblock’, ‘correlation’, ‘cosine’, ‘dice’, ‘euclidean’, ‘hamming’, ‘jaccard’, ‘jensenshannon’, ‘kulsinski’, ‘mahalanobis’, ‘matching’, ‘minkowski’, ‘rogerstanimoto’, ‘russellrao’, ‘seuclidean’, ‘sokalmichener’, ‘sokalsneath’, ‘sqeuclidean’, ‘wminkowski’, ‘yule’.

  • anno_filter (str, optional (default: None)) – The annotation of filter to use. It should be one of adata.obs_keys()

  • filter_gene (str, optional (default: None)) – The filter for gene. It should be in adata.obs[anno_filter]

  • metrics_gene (pandas.DataFrame, optional (default: None)) – SIMBA metrics for genes.

  • metrics_motif (pandas.DataFrame, optional (default: None)) – SIMBA metrics for motifs.

  • cutoff_gene_max (float) – cutoff of SIMBA metric max value for genes and motifs

  • cutoff_motif_max (float) – cutoff of SIMBA metric max value for genes and motifs

  • cutoff_gene_gini (float) – cutoff of SIMBA metric Gini index for genes and motifs

  • cutoff_motif_gini (float) – cutoff of SIMBA metric Gini index for genes and motifs

  • cutoff_gene_gini – cutoff of SIMBA metric Gini index for genes and motifs

  • cutoff_motif_gini – cutoff of SIMBA metric Gini index for genes and motifs

  • cutoff_gene_std (float) – cutoff of SIMBA metric standard deviation for genes and motifs

  • cutoff_motif_std (float) – cutoff of SIMBA metric standard deviation for genes and motifs

  • cutoff_gene_entropy (float) – cutoff of SIMBA metric entropy for genes and motifs

  • cutoff_motif_entropy (float) – cutoff of SIMBA metric entropy for genes and motifs

Returns:

df_MR – Dataframe of master regulators

Return type:

pandas.DataFrame