clusteringKmeans {seqsetvis}R Documentation

perform kmeans clustering on matrix rows and return reordered matrix along with order matched cluster assignments. clusters are sorted using hclust on centers

Description

perform kmeans clustering on matrix rows and return reordered matrix along with order matched cluster assignments. clusters are sorted using hclust on centers

Usage

clusteringKmeans(mat, nclust, centroids = NULL)

Arguments

mat

numeric matrix to cluster.

nclust

the number of clusters.

centroids

optional matrix with same columns as mat and one centroid per row to base clusters off of. Overrides any setting to nclust. Default of NULL results in randomly initialized k-means.

Value

data.table with group variable indicating cluster membership and id variable that is a factor indicating order based on within cluster similarity

Examples

dt = data.table::copy(CTCF_in_10a_profiles_dt)
mat = data.table::dcast(dt, id ~ sample + x, value.var = "y" )
rn = mat$id
mat = as.matrix(mat[,-1])
rownames(mat) = rn
clust_dt = clusteringKmeans(mat, nclust = 3)
dt = merge(dt, clust_dt)
dt$id = factor(dt$id, levels = clust_dt$id)
dt[order(id)]

[Package seqsetvis version 1.12.0 Index]