clusteringKmeansNestedHclust: 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 the contents of each cluster are sorted using hclust

Usage

clusteringKmeansNestedHclust(
  mat,
  nclust,
  within_order_strategy = c("hclust", "sort")[2],
  seed = NULL
)

Arguments

mat	A wide format matrix
nclust	the number of clusters
within_order_strategy	one of "hclust" or "sort". if hclust, hierarchical clustering will be used. if sort, a simple decreasing sort of rosSums.
seed	passed to set.seed() to allow reproducibility

Value

data.table with 2 columns of cluster info. id column corresponds with input matrix rownames and is sorted within each cluster using hierarchical clusering group column indicates cluster assignment

Examples

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

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