scanpy.pp.filter_genes

scanpy.pp.filter_genes(data, min_counts=None, min_cells=None, max_counts=None, max_cells=None, inplace=True, copy=False)

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
data : AnnDataAnnData

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

min_counts : int, NoneOptional[int] (default: None)

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

min_cells : int, NoneOptional[int] (default: None)

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

max_counts : int, NoneOptional[int] (default: None)

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

max_cells : int, NoneOptional[int] (default: None)

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

inplace : boolbool (default: True)

Perform computation inplace or return result.

Return type

AnnData, None, Tuple[ndarray, ndarray]Union[AnnData, None, Tuple[ndarray, ndarray]]

Returns

Depending on inplace, returns the following arrays or directly subsets and annotates the data matrix

gene_subsetndarray

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

number_per_genendarray

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