cat.compare

Contents

cat.compare#

cat.compare(ds1: Dataset, ds2: Dataset, n_iterations: int = 1000, features: list[str] | None = None, distance: str = 'euclidean') → DatasetDiff#

CAT routine calculated the inter cluster distances. The order of dataset1 and dataset2 does not matter.

Parameters:

  • dataset1 (Dataset) – First dataset, must contain anndata, with labels for each cluster in an obs variable “XXX”. Should be normalized.

  • dataset2 (Dataset) – Second dataset, must contain anndata, with labels for each cluster in an obs variable “XXX”. Should be normalized.

  • n_iterations (int, optional) – Number of iterations in the bootstrap process, by default ‘value’

  • features (list[str], optional) – Subset of gene names (i.e. GO:TERM)

  • distance (str) – Euclidean distance, by default euclidean

Returns:

A table containing the distances of each cluster relative to every other cluster

Return type:

Pandas DataFrame

Contents