phlower.ext.ddhodge

phlower.ext.ddhodge(adata: AnnData, basis: str = 'X_pca', roots: str | list | None = None, k: int = 11, npc: int = 100, ndc: int = 40, s: int = 1, j: int = 7, lmda: float = 0.0001, sigma: float | None = None, layout: str = 'neato', iscopy: bool = False, verbose: bool = True, lstsq_method: str = 'lstsq')

ddhodge implementation for dimension reduction.

Parameters

basis

Name of the basis to use for dimension reduction if None use normalization from ddhodge to perform pca.

roots

Root cells for diffusion graph construction.

k

Number of nearest neighbors for graph prunning.

npc

Number of principal components for diffusion graph construction.

ndc

Number of diffusion components for diffusion graph construction.

s

Number of diffusion steps for diffusion graph construction.

j

Number of nearest neighbors for diffusion graph construction.

lmda

Regularization parameter for edge weights.

layout

Graphviz layout to use for visualization, can be one of ‘dot’, ‘neato’, ‘fdp’, ‘sfdp’, ‘twopi’, ‘circo’.

lstsq_method

Diffusion psuedo time estimation method, can be one of ‘lstsq’, ‘lsqr’, ‘lsmr’, ‘cholesky’.