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Initial Clustering

Source: R/initialClustering.R
initialClustering.Rd

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 seu@meta.data 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 seu@meta.data 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