commot.tl.communication_deg_clustering

commot.tl.communication_deg_clustering(df_deg, df_yhat, deg_clustering_npc=10, deg_clustering_knn=5, deg_clustering_res=1.0, n_deg_genes=200, p_value_cutoff=0.05)

Cluster the communcation DE genes based on their fitted expression pattern.

Parameters

  • df_deg (DataFrame) – The deg analysis summary data frame obtained by running communication_deg_detection. Each row corresponds to one tested genes and columns include “waldStat” (Wald statistics), “df” (degrees of freedom), and “pvalue” (p-value of the Wald statistics).

  • df_yhat (DataFrame) – The fitted (smoothed) gene expression pattern obtained by running tl.communication_deg_detection.

  • deg_clustering_npc (int) – Number of PCs when performing PCA to cluster gene expression patterns

  • deg_clustering_knn (int) – Number of neighbors when constructing the knn graph for leiden clustering.

  • deg_clustering_res (float) – The resolution parameter for leiden clustering.

  • n_deg_genes (int) – Number of top deg genes to cluster.

  • p_value_cutoff (float) – The p-value cutoff for genes to be included in clustering analysis.

Returns

  • df_deg_clus (pd.DataFrame) – A data frame of clustered genes.

  • df_yhat_clus (pd.DataFrame) – The fitted gene expression patterns of the clustered genes