KClustDimension: Perform spectral k-means clustering on single cells
Description
Find point clounds single cells in a low-dimensional space using k-means clustering.
Can be useful for smaller datasets, where graph-based clustering can perform poorly
Usage
KClustDimension(object, dims.use = c(1, 2), reduction.use = "tsne",
k.use = 5, set.ident = TRUE, seed.use = 1)
Arguments
dims.use
Dimensions to use for clustering
reduction.use
Dimmensional Reduction to use for k-means clustering
set.ident
Set identity of Seurat object
Value
Object with clustering information
Examples
Run this code# NOT RUN {
pbmc_small
# K-means clustering on the first two tSNE dimensions
pbmc_small <- KClustDimension(pbmc_small)
# }
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