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Apply per-gene multiple testing correction for site selection metrics #460

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Apply per-gene multiple testing correction for site selection metrics #460

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Copilot May 21, 2026
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Add per-gene multiple testing correction for site comparisons
Copilot May 21, 2026
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18 changes: 18 additions & 0 deletions bin/omega_comparison_per_site.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,6 +32,17 @@ def poisson_pvalue(observed, expected):
"""
return 1 - stats.poisson.cdf(observed - 1, expected)

def benjamini_hochberg(pvals):
if pvals.size == 0:
return pvals
order = np.argsort(pvals)
ranked = np.arange(1, pvals.size + 1)
adjusted = np.empty_like(pvals, dtype=float)
adjusted[order] = pvals[order] * pvals.size / ranked
adjusted_sorted = np.minimum.accumulate(adjusted[order][::-1])[::-1]
adjusted[order] = adjusted_sorted
return np.clip(adjusted, 0.0, 1.0)

def compute_by_size(panel, mutations, mutabilities, size, sample_column):
# Merge mutations and panel to associate protein positions
mutations = mutations.merge(panel[['CHROM', 'POS', 'REF', 'ALT', 'Protein_position', 'Amino_acids', 'GENE', 'Feature']],
Expand Down Expand Up @@ -66,6 +77,13 @@ def compute_by_size(panel, mutations, mutabilities, size, sample_column):
result["OBS/EXP"] = (result["OBSERVED_MUTS"] / result["EXPECTED_MUTS"]).fillna(0)
result["OBS/EXP"] = result["OBS/EXP"].replace([np.inf, -np.inf], 0)
result["p_value"] = result[["OBSERVED_MUTS", "EXPECTED_MUTS"]].apply(lambda row: poisson_pvalue(row["OBSERVED_MUTS"], row["EXPECTED_MUTS"]), axis=1)
result["p_value_adj"] = np.nan
for gene, gene_df in result.groupby("GENE", dropna=False):
valid_mask = gene_df["p_value"].notna()
if not valid_mask.any():
continue
adjusted = benjamini_hochberg(gene_df.loc[valid_mask, "p_value"].to_numpy())
result.loc[gene_df.index[valid_mask], "p_value_adj"] = adjusted

return result

Expand Down