simba.tl.umap

simba.tl.umap(adata, n_neighbors=15, n_components=2, random_state=2020, layer=None, obsm=None, n_dim=None, **kwargs)[source]

perform UMAP :param adata: Annotated data matrix. :type adata: AnnData :param n_neighbors: The size of local neighborhood for UMAP :type n_neighbors: int, optional (default: 15) :param n_components: The dimension of the space to embed into for UMAP :type n_components: int, optional (default: None) :param random_state: The seed used by the random number generator for UMAP :type random_state: int, optional (default: None) :param layer: The layer used to perform UMAP :type layer: str, optional (default: None) :param obsm: The multi-dimensional annotation of observations used to perform UMAP :type obsm: str, optional (default: None) :param n_dim: The number of dimensions used in layer or obsm :type n_dim: str, optional (default: None) :param kwargs: Other keyword arguments are passed down to umap_learn.UMAP

Returns:

updates adata with the following fields
`.obsm[‘X_umap’]` (array) – UMAP coordinates of samples.