- stlearn.pp.filter_genes(adata: AnnData, min_counts: Optional[int] = None, min_cells: Optional[int] = None, max_counts: Optional[int] = None, max_cells: Optional[int] = None, inplace: bool = True) Union[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. :param data: 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.
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.