cellrank.tl.estimators.GPCCA.lineage_drivers

property GPCCA.lineage_drivers: Optional[pandas.core.frame.DataFrame]

Potential lineage drivers.

Computes Pearson correlation of each gene with fate probabilities for every terminal state. High Pearson correlation indicates potential lineage drivers. Also computes p-values and confidence intervals.

Return type

Optional[DataFrame]

Returns

Dataframe of shape (n_genes, n_lineages * 5) containing the following columns, one for each lineage:

• {lineage}_corr - correlation between the gene expression and absorption probabilities.

• {lineage}_pval - calculated p-values for double-sided test.

• {lineage}_qval - corrected p-values using Benjamini-Hochberg method at level 0.05.

• {lineage}_ci_low - lower bound of the confidence_level correlation confidence interval.

• {lineage}_ci_high - upper bound of the confidence_level correlation confidence interval.