mods.detect: Wrapper for weighted gene co-expression analysis

In montilab/shine: Structure Learning for Hierarchical Networks

Description

Wrapper for weighted gene co-expression analysis

Usage

mods.detect(
  eset,
  min.size = 10,
  min.sft = 0.85,
  beta = NULL,
  cores = 1,
  cor.fn = c("bicor", "cor"),
  powers = c(seq(1, 10, by = 1), seq(12, 20, by = 2)),
  merging = FALSE,
  merging.cut = 0.2,
  hclust.method = "average",
  do.plot = TRUE
)

Arguments

eset	An expression set object
min.size	Minimum module size
min.sft	Minimum acceptable scale-free fit when choosing soft threshold
beta	Override soft thresholding choice
cores	Number of cpus to use
cor.fn	Method for calculation co-expression similarity
powers	A vector of values to test for soft thresholding
merging	Merge similar modules by eigengene
merging.cut	Maximum dissimilarity that qualifies modules for merging
hclust.method	Clustering method passed to hclust
do.plot	Use true to see plots

Value

A list of data pertaining to resulting co-expression modules

montilab/shine documentation built on May 20, 2021, 4:22 p.m.