K-Means clustering

Source: R/03_NB_based_cell_comparison.R

ISCHIA-inspired K-Means clustering

kmeans_clust(data = NULL, n_clust = 1:10, label = NULL, seed = 347548)

Arguments

data

Seurat object containing Kandinsky data

n_clust

numeric, number of expected clusters. Can be a single number or a numeric vector if multiple cluster numbers needs to be tested

label

character string specifying the variable name to be used to defne cell annotation groups

seed

numeric, random seed.

Value

updated Seurat object with 'kmeans_clusters' annotation added to metadata slot

Details

When more than one cluster configurations are provided, the function chooses the one minimizing Within-Cluster Sum of Squares (WSS), as implemented in the R package ISCHIA