scmagnify.tools.test_association

scmagnify.tools.test_association#

scmagnify.tools.test_association(data, modal='RNA', layer='log1p_norm', time_key='palantir_pseudotime', n_splines=5, max_iter=100, tol=0.0001, fdr_cutoff=0.001, A_cutoff=0.5, n_jobs=10, recompute=False)#

Test association between genes and pseudotime, and optionally re-filter significant genes.

Parameters:

  • data (AnnData | MuData | GRNMuData) – Single cell data object. Can be an anndata.AnnData, mudata.MuData, scmagnify.GRNMuData

  • modal (str | None (default: 'RNA')) – Modality key (e.g., ‘RNA’, ‘ATAC’) when using multi-modal data. mudata.MuData or scmagnify.GRNMuData must be provided.

  • layer (str | None (default: 'log1p_norm')) – Layer in layers. If None, defaults to X.

  • time_key (str (default: 'palantir_pseudotime')) – Key in obs that stores pseudotime values.

  • n_splines (int (default: 5)) – Number of splines for GAM smoothing.

  • max_iter (int (default: 100)) – Maximum number of iterations used by pygam fitting. Default is 100.

  • tol (float (default: 0.0001)) – Tolerance for pygam convergence. Default is 1e-4.

  • fdr_cutoff (float (default: 0.001)) – False discovery rate cutoff. Default is 1e-3.

  • A_cutoff (float (default: 0.5)) – Amplitude cutoff. Default is 0.5.

  • n_jobs (int (default: 10)) – Number of parallel jobs to run. If -1, use all available cores.

  • recompute (bool (default: False)) – If True, recompute the association test. If False, use existing results.

Return type:

AnnData | MuData

Returns:

Union[AnnData, MuData] Annotated data matrix with the results stored in adata.varm[“test_assoc_res”].

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