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Performs subsampling-based consensus clustering across multiple resolution parameters to identify robust cluster numbers in single-cell RNA-seq data.

Usage

MultiK(
  seu,
  resolution = seq(0.05, 2, 0.05),
  nPC = 30,
  reps = 100,
  pSample = 0.8,
  k.param = 20,
  nfeatures = 2000,
  seed = NULL,
  cores = 1
)

Arguments

seu

A Seurat object

resolution

Numeric vector of resolution parameters for Seurat clustering. Default is seq(0.05, 2, 0.05)

nPC

Number of principal components. Default is 30

reps

Number of subsampling iterations. Default is 100

pSample

Proportion of cells to subsample. Default is 0.8

k.param

Number of nearest neighbors for graph construction. Default is 20

nfeatures

Number of variable features to select. Default is 2000

seed

Random seed for reproducibility. Default is NULL

cores

Number of cores for parallel processing. Default is 1

Value

A list containing:

k

Vector of K values from all clustering runs

clusters

Clustering results for each K

consensus

Consensus matrix for each K