hucira.run_all_enrichment_test

hucira.run_all_enrichment_test#

hucira.run_all_enrichment_test(adata, df, celltype_combos, celltype_column, contrasts_combo, contrast_column, direction='upregulated', threshold_lfc=1.0, threshold_expression=0.0, threshold_pval=0.01, min_size=10, max_size=1000, permutation_num=1000, weight=1.0, seed=2025, verbose=False, threads=6)#

Compute cytokine enrichment across multiple threshold values for robustness.

Wrapper around run_one_enrichment_test() that loops through several threshold values to obtain more robust results.

Parameters:

  • adata (AnnData) – The query AnnData object.

  • df (pandas.DataFrame) – Human Cytokine Dictionary, CIP signatures, or custom gene-program DataFrame.

  • celltype_combos (list of tuple) – List of (query_celltype, df_celltype) pairs.

  • celltype_column (str) – Column name in adata.obs that stores the cell types.

  • contrasts_combo (tuple of (str, str) or list of tuple) – Pair(s) of biological conditions to compare.

  • contrast_column (str) – Column name in adata.obs that stores condition labels.

  • direction (str) – One of "upregulated", "downregulated", or "both".

  • threshold_lfc (float or list of float) – Log-fold change threshold(s) for building the gene set.

  • threshold_expression (float or list of float) – Mean gene-expression threshold(s).

  • threshold_pval (float) – Maximum adjusted p-value for the gene set.

  • min_size (int) – Minimum gene-set size passed to GSEA.

  • max_size (int) – Maximum gene-set size passed to GSEA.

  • permutation_num (int) – Number of permutations for GSEA.

  • weight (float) – GSEA weighting exponent.

  • seed (int) – Random seed for reproducibility.

  • verbose (bool) – Whether to print progress messages.

  • threads (int) – Number of threads for GSEA.

Return type:

DataFrame

Returns:

pandas.DataFrame DataFrame with all computed enrichment scores and statistical parameters from multiple thresholds.

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