dycutdf: Hierarchical clustering using amp, and split dataframe by...

In shkonishi/cornet: Cunstruction of correlation network form transcriptome data

Description

dycutdf

Usage

dycutdf(dat, distm, clm, column, method_dycut, ...)

Arguments

dat	data frame or matrix
distm	distance measure from amap::Dist options. default is "pearson"
clm	clustering method select from hclust options default is "average"
column	column which containing expression data default 'column=1:ncol(dat)'
method_dycut	method of dynamic cut, otherwise k number of cuttree function.
...	character additional dynamicTreeCut::cutreeDynamic options. E.g. "minClusterSize = 10"

Value

list of results of clustering, objects was hclust, dendrogram, and list of splitted data.frame

Examples

d <- data.frame(t(iris[-5]))
res <- dycutdf(dat = d, distm = "euclidean", clm = "average",
               column = 1:150, method_dycut = "hybrid")
res[[1]] # hclust object
res[[2]] # dendrogram object
res[[3]] # result of dynamic cut object
res[[4]] # list of splitted data.frame

##  The following examples takes too much times
# nfpkm <- rskodat::nfpkm
# res1 <- cornet::dycutdf(dat = nfpkm, distm = "abscorrelation", clm = "average",
#     column = 5:ncol(nfpkm), method_dycut = "tree")

shkonishi/cornet documentation built on May 30, 2019, 7:09 p.m.