getDistMat: Calculate the Similarity Matrix

In zhiyhu/CIDER: Meta-Clustering for Single-Cell Data Integration and Evaluation

Calculate the Similarity Matrix

Description

Compute the IDER-based similarity matrix for a list of Seurat objects. This function does not regress out batch effects and is designed to be used at the initial clustering step.

Usage

getDistMat(
  seu_list,
  verbose = TRUE,
  tmp.initial.clusters = "seurat_clusters",
  method = "trend",
  additional.variate = NULL,
  downsampling.size = 35,
  downsampling.include = TRUE,
  downsampling.replace = TRUE
)

Arguments

seu_list	A list containing Seurat objects. Required.
verbose	Print the message and progress bar (default: TRUE)
tmp.initial.clusters	One of the colnames from '[e-mail]'. Used as the group. Default: "seurat_clusters"
method	Methods for DE analysis. Options: "voom" or "trend" (default)
additional.variate	additional variate to include into the linear model to regress out
downsampling.size	Number of cells used per group. Default: 35
downsampling.include	Whether to include the group of size smaller than 'downsampling.size'. Default: TRUE
downsampling.replace	Whether to use 'replace' in sampling for group of size smaller than 'downsampling.size' if they are kept. Default: TRUE

Value

A list of similarity matrices

Author(s)

Zhiyuan Hu

See Also

calculateDistMatOneModel

zhiyhu/CIDER documentation built on Feb. 4, 2025, 1:09 a.m.