hest.get_k_genes

hest.get_k_genes(adata_list: List[sc.AnnData], k: int, criteria: str, save_dir: str = None, min_cells_pct=0.1) → List[str]

Get the top-k genes according to some criteria in common genes across multiple samples. This function was used to derive genes of interest for the HEST benchmark.

Parameters:

  • adata_list (List[sc.AnnData]) – list of scanpy AnnData containing gene expressions in adata.to_df()

  • k (int) – number of most genes to return

  • criteria (str) – criteria for the k genes to return - ‘mean’: return the k genes with the largest mean expression across samples - ‘var’: return the k genes with the largest expression variance across samples

  • save_dir (str, optional) – genes are saved as json array to this path if not None. Defaults to None.

  • min_cells_pct (float) – filter out genes that are expressed in less than min_cells_pct% of the spots for each slide

Returns:

top-k genes according to the criteria

Return type:

List[str]

Examples

>>> # Find genes for interest for HEST benchmark
>>> import scanpy as sc
>>> from hest import get_k_genes
>>> ad1 = sc.read_h5ad("TENX118.h5ad")
>>> ad2 = sc.read_h5ad("TENX141.h5ad")
>>> genes = get_k_genes([ad1, ad2], k=50, criteria="var")
>>> print(len(genes))