RunDiffusion: Run Diffusion map

In Morriseylab/scExtras: Single cell data analysis helper functions

Run Diffusion map

Description

Run Diffusion map

Usage

RunDiffusion(
  object,
  dims = 1:5,
  reduction = "pca",
  features = NULL,
  max.dim = 3L,
  sigma = "local",
  distance = "euclidean",
  reduction.name = "dm",
  reduction.key = "DM_",
  ...
)

Arguments

object	Seurat object
dims	number of dimensions
reduction	reductionm method. Defaults to pca
features	vector of gene names
max.dim	maximum dimensions
sigma	Diffusion scale parameter of the Gaussian kernel. One of 'local', 'global', a (numeric) global sigma or a Sigmas object. When choosing 'global', a global sigma will be calculated using find_sigmas. (Optional. default: 'local') A larger sigma might be necessary if the eigenvalues can not be found because of a singularity in the matrix
distance	Distance measurement method applied to data or a distance matrix/dist. For the allowed values, see find_knn. If this is a sparseMatrix, zeros are interpreted as "not a close neighbors", which allows the use of kNN-sparsified matrices (see the return value of find_knn.
reduction.name	Dimension Reduction method
reduction.key	Dimension Reduction key

Morriseylab/scExtras documentation built on July 10, 2024, 6:41 a.m.