cellink.tl.run_burden_test

cellink.tl.run_burden_test(G, Y, F, gene, annotation_cols, burden_agg_fct='sum', run_lrt=True)

Perform a burden test for genetic association analysis.

Parameters:

• G (AnnData) – An AnnData object containing genotype data. The X attribute should contain the genotype matrix, and the varm["variant_annotation"] attribute should contain variant annotations.

• Y (np.ndarray) – Phenotype data for the samples.

• F (np.ndarray) – Covariate matrix for the samples.

• gene (str) – The name of the gene being tested.

• annotation_cols (list of str) – List of column names in G.varm["variant_annotation"] to use for calculating variant scores.

• burden_agg_fct (str (default="sum")) – Aggregation function to compute the burden score. Options include “sum”, “mean”, “max”.

• run_lrt (bool (default=True)) – Whether to compute the likelihood ratio test (LRT) for the burden test.

Returns:

-rdf (DataFrame) A DataFrame containing the results of the burden test with the following columns: - “burden_gene”: The gene name whose burden was used. - “egene”: The gene name that was tested (expression, Y). - “weight_col”: The annotation columns used for the burden test. - “burden_agg_fct”: The aggregation function used. - “pv”: P-values from the GWAS analysis. - “beta”: Effect sizes from the GWAS analysis. - “betaste”: Standard errors of the effect sizes. - “lrt” (if run_lrt is True): LRT statistics from the GWAS analysis.