tidesurf.counter.UMICounter.count

UMICounter.count(bam_file: str, filter_cells: bool = False, whitelist: Optional[str] = None, num_umis: int = -1) → Tuple[ndarray, ndarray, Dict[str, csr_matrix]]

Count UMIs with reads mapping to transcripts.

Parameters:

bam_file str

Path to BAM file.

filter_cells bool

Whether to filter cells (default: False).

whitelist str | None

If filter_cells is True: path to cell barcode whitelist file. Mutually exclusive with num_umis (default: None).

num_umis int

If filter_cells is True: set to an integer to only keep cells with at least that many UMIs. Mutually exclusive with whitelist (default: -1; corresponds to not filtering based on number of UMIs).

Returns:

Cells (array of shape (n_cells,)), genes (array of shape (n_genes,)), counts (dictionary with sparse matrices of shape (n_cells, n_genes) for spliced, unspliced, and ambiguous).

Return type:

Tuple[ndarray, ndarray, Dict[str, csr_matrix]]