nb_mcupgma: Calculate dendrogram for a sparse distance matrix (external...

In netboost: Network Analysis Supported by Boosting

Description

Calculate dendrogram for a sparse distance matrix (external wrapper MC-UPGMA clustering package Loewenstein et al.

Usage

nb_mcupgma(filter, dist, max_singleton, cores = getOption("mc.cores",
  2L), verbose = getOption("verbose"))

Arguments

filter	Filter-Matrix as generated by the nb_filter function.
dist	Distance-Matrix as generated by the nb_dist function.
max_singleton	Integer The maximal singleton in the clustering. Usually equals the number of features.
cores	Integer Amount of CPU cores used (<=1 : sequential)
verbose	Logical Additional diagnostic messages.

Value

Raw dendrogram to be processed by tree_search and tree_dendro.

Examples

   data('tcga_aml_meth_rna_chr18', package='netboost')
   cores <- as.integer(getOption('mc.cores', 2))
   datan <- as.data.frame(scale(tcga_aml_meth_rna_chr18,
   center=TRUE, scale=TRUE))
   filter <- nb_filter(datan=datan, stepno=20L, until=0L,
                       progress=1000L, cores=cores, mode=2L)
   dist <- nb_dist(datan=datan, filter=filter, soft_power=3L, cores=cores)
   max_singleton = dim(tcga_aml_meth_rna_chr18)[2]
   forest <- nb_mcupgma(filter=filter, dist=dist,
                        max_singleton=max_singleton, cores=cores)
 head(forest)

netboost documentation built on Nov. 8, 2020, 4:58 p.m.