clusteringKmeans: perform kmeans clustering on matrix rows and return reordered...

In seqsetvis: Set Based Visualizations for Next-Gen Sequencing Data

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, seed = NULL)

Arguments

mat	numeric matrix to cluster
nclust	the number of clusters
seed	DEPRECATED. Call set.seed() prior to this funciton to allow reproducibility.

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)]

seqsetvis documentation built on Nov. 8, 2020, 5:57 p.m.