getDistMat: Calculate the Similarity Matrix

In CIDER: Meta-Clustering for scRNA-Seq 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 for use during the initial clustering step.

Usage

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

Arguments

seu_list	A list containing Seurat objects. Required.
verbose	Logical. If TRUE, progress messages and a progress bar are displayed. Default is TRUE.
tmp.initial.clusters	Character string specifying one of the column names from [e-mail] that denotes groups, e.g., initial clusters. Default is "seurat_clusters".
method	Character string specifying the method for differential expression analysis. Options are "voom" or "trend" (default is "trend").
batch.var	Character string specifying the metadata column containing batch information. Default is "Batch".
additional.variate	Character vector of additional variates to include in the linear model for regression.
downsampling.size	Numeric value indicating the number of cells to use per group. Default is 35.
downsampling.include	Logical. Whether to include groups with fewer cells than downsampling.size. Default is TRUE.
downsampling.replace	Logical. Whether to sample with replacement for groups smaller than downsampling.size. Default is TRUE.

Value

A list of similarity matrices.

See Also

calculateDistMatOneModel

CIDER documentation built on April 4, 2025, 2:28 a.m.