findModules.consensusKmeans: Finds Moduless With Kmeans Clustering

In Sage-Bionetworks/metanetwork: Network meta analysis

Finds Moduless With Kmeans Clustering

Description

Function to get consensus modules from individual partition matrices

Usage

findModules.consensusKmeans(
  partition.adj,
  min.module.size = 20,
  usepam = FALSE
)

Arguments

partition.adj	Required. A partition.adj = n x m adjacency matrix, where n is the number of genes and m = number of clustering methods * number of clusters in each method.
min.module.size	Optional. An integer between 1 and n genes (Default = 20)
usepam	Optional. A logical for input into pam based kmeans clustering to find the number of clusters with the function 'fpc::pamk'. If TRUE, pam is used, otherwise clara (recommended for large datasets with 2,000 or more observations; dissimilarity matrices can not be used with clara). (Default = 20)

Value

A dataframe of Gene Modules

Sage-Bionetworks/metanetwork documentation built on April 27, 2022, 7:42 a.m.