[docs]deffilter_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[np.ndarray,np.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. """returnscanpy.pp.filter_genes(adata,min_counts=min_counts,min_cells=min_cells,max_counts=max_counts,max_cells=max_cells,inplace=inplace,)