stlearn.pp.filter_genes

stlearn.pp.filter_genes(adata: AnnData, min_counts: int | None = None, min_cells: int | None = None, max_counts: int | None = None, max_cells: int | None = None, inplace: bool = True) → AnnData | None | tuple[ndarray, ndarray]

Wrap function scanpy.pp.filter_genes

Filter genes based on number of cells or counts.

Keep genes that have at least min_counts counts or are expressed in at least min_cells cells or have at most max_counts counts or are expressed in at most max_cells cells.

Only provide one of the optional parameters min_counts, min_cells, max_counts, max_cells per call.

Parameters:

• adata – An annotated data matrix of shape n_obs × n_vars. Rows correspond to cells and columns to genes.

• min_counts – Minimum number of counts required for a gene to pass filtering.

• min_cells – Minimum number of cells expressed required for a gene to pass filtering.

• max_counts – Maximum number of counts required for a gene to pass filtering.

• max_cells – Maximum number of cells expressed required for a gene to pass filtering.

• inplace – Perform computation inplace or return result.

Returns:

• Depending on inplace, returns the following arrays or directly subsets

• and annotates the data matrix

• gene_subset – Boolean index mask that does filtering. True means that the gene is kept. False means the gene is removed.

• number_per_gene – Depending on what was tresholded (counts or cells), the array stores n_counts or n_cells per gene.