initialClustering: Initial Clustering

In CIDER: Meta-Clustering for scRNA-Seq Integration and Evaluation

Initial Clustering

Description

Perform batch-specific initial clustering on a Seurat object.

Usage

initialClustering(
  seu,
  batch.var = "Batch",
  cut.height = 0.4,
  nfeatures = 2000,
  additional.vars.to.regress = NULL,
  dims = seq_len(14),
  resolution = 0.6,
  downsampling.size = 50,
  verbose = FALSE
)

Arguments

seu	A Seurat object. Required.
batch.var	Character string specifying one of the column names in [e-mail] used to partition the object into subsets. Default is "Batch".
cut.height	Numeric value specifying the height at which to cut hierarchical trees. Default is 0.4.
nfeatures	Numeric value indicating the number of high-variance genes to use. Default is 2000.
additional.vars.to.regress	Character vector of additional variable names from [e-mail] to regress out. Optional. Default is NULL.
dims	Numeric vector specifying the dimensions to be used for clustering (passed to Seurat). Default is 1:14.
resolution	Numeric value for clustering resolution (passed to Seurat). Default is 0.6.
downsampling.size	Numeric value indicating the number of cells representing each group. Default is 40.
verbose	Logical. If TRUE, a progress bar is displayed. Default is FALSE.

Value

A Seurat S4 object with initial cluster assignments stored in the initial_cluster column of its meta.data.

See Also

getIDEr, finalClustering

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