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)