Wrapper for weighted gene co-expression analysis

Wrapper for weighted gene co-expression analysis

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