scFates.pp.diffusion#
- scFates.pp.diffusion(adata, n_components=10, knn=30, alpha=0, multiscale=True, n_eigs=None, device='cpu', n_pcs=50, save_uns=False, copy=False)#
Wrapper to generate diffusion maps using Palantir.
- Parameters:
- adata
AnnData Annotated data matrix.
- n_components
int(default:10) Number of diffusion components.
- knn
int(default:30) Number of nearest neighbors for graph construction.
- alpha
float(default:0) Normalization parameter for the diffusion operator.
- multiscale
bool(default:True) Whether to get mutliscale diffusion space (calls palantir.utils.determine_multiscale_space).
- n_eigs
Optional[int] (default:None) if multiscale is True, how much components to retain.
- device
Literal['cpu','gpu'] (default:'cpu') Run method on either cpu or on gpu.
- do_PCA
Whether to perform PCA or not.
- n_pcs
int(default:50) Number of PC components.
- seed
Get reproducible results for the GPU implementation.
- copy
bool(default:False) Return a copy instead of writing to adata.
- adata
- Returns:
adata : anndata.AnnData if copy=True it returns AnnData, else it update field to adata:
- .obsm[‘X_diffusion’]
if multiscale = False, diffusion space.
- .obsm[‘X_multiscale_diffusion’]
if multiscale = True, multiscale diffusion space.
- .uns[‘diffusion’]
dict containing results from Palantir.