def test_aucell_mismatch(exp_matrix, gs): percentiles = derive_auc_threshold(exp_matrix) gss = [ GeneSignature(name="test", gene2weight=list(map("FAKE{}".format, range(100)))) ] + gs aucs_mtx = aucell(exp_matrix, gss, auc_threshold=percentiles[0.01], num_workers=1) print(aucs_mtx.head())
def test_aucell_w2(): ex_mtx = exp_matrix() percentiles = derive_auc_threshold(ex_mtx) aucs_mtx = aucell(ex_mtx, gs(), auc_threshold=percentiles[0.01], num_workers=4)
args = parser_grn.parse_args() # Do stuff ex_matrix_df = utils.get_matrix(loom_file_path=args.expression_mtx_fname.name, gene_attribute=args.gene_attribute, cell_id_attribute=args.cell_id_attribute) signatures = utils.read_signatures_from_tsv_dir( dpath=args.signatures_fname, noweights=False, weight_threshold=args.min_regulon_gene_occurrence, min_genes=args.min_genes) if len(signatures) == 0: raise Exception( f"No signature passing filtering. Please consider to adapt 'min_genes_regulon = {args.min_genes_regulon}' and 'min_regulon_gene_occurrence = {args.min_regulon_gene_occurrence}' (see params.sc.scenic.aucell). Make sure these settings are smaller than numRuns (params.sc.scenic)." ) auc_threshold = args.auc_threshold if args.percentile_threshold is not None: percentiles = derive_auc_threshold(ex_matrix_df) auc_threshold = percentiles[args.percentile_threshold] aucs_mtx = aucell(ex_matrix_df, signatures, auc_threshold=auc_threshold, num_workers=args.num_workers) aucs_mtx.to_csv(path_or_buf=args.output, index=True, sep='\t')
def test_aucell_w2(exp_matrix, gs): percentiles = derive_auc_threshold(exp_matrix) aucs_mtx = aucell(exp_matrix, gs, auc_threshold=percentiles[0.01], num_workers=4)