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Compute IDER-Based Similarity

Source: R/getIDER.R
getIDEr.Rd

Calculate the similarity matrix based on Inter-group Differential Expression (IDER) metrics with the selected batch effects regressed out.

Usage

getIDEr(
  seu,
  group.by.var = "initial_cluster",
  batch.by.var = "Batch",
  verbose = TRUE,
  use.parallel = FALSE,
  n.cores = 1,
  downsampling.size = 40,
  downsampling.include = TRUE,
  downsampling.replace = TRUE
)

Arguments

seu

A Seurat S4 object that includes an initial_cluster column in its meta.data. Required.

group.by.var

Character string specifying the column in seu@meta.data that defines initial clusters (batch-specific groups). Default is "initial_cluster".

batch.by.var

Character string specifying the metadata column that indicates batch information. Default is "Batch".

verbose

Logical. If TRUE, progress messages and a progress bar are displayed. Default is TRUE.

use.parallel

Logical. If TRUE, parallel computation is used (requires doParallel); in this case, no progress bar will be shown. Default is FALSE.

n.cores

Numeric. The number of cores to use for parallel computing. Default is 1.

downsampling.size

Numeric. The number of cells representing each group. Default is 40.

downsampling.include

Logical. Whether to include groups with fewer cells than downsampling.size. Default is FALSE.

downsampling.replace

Logical. Whether to sample with replacement if a group is smaller than downsampling.size. Default is FALSE.

Value

A list of objects: a similarity matrix, a numeric vector recording the cells used, and a data frame of the group combinations included.

See also

plotNetwork, finalClustering