Auto_WGCNA {GmicR} | R Documentation |
Carries out WGCNA with default settings or custom settings
Auto_WGCNA( datExpr, colname_correct = TRUE, minModuleSize = 10, deepSplit = 4, networkType = "signed hybrid", TOMType = "unsigned", corFnc = "bicor", mergeCutHeight = 0.25, sft_RsquaredCut = 0.85, reassignThreshold = 1e-06, maxBlockSize = 25000 )
datExpr |
Expression data. A matrix (preferred) or
data frame in which columns are genes and rows ar samples. NAs are
allowed, but not too many. See |
colname_correct |
a logical value. If TRUE (default), "." in gene names will be replaced with "-". This corrects a name change that is induced by R when creating a data.frame. If FALSE, no changes will be made. |
minModuleSize |
minimum module size for module detection. See
|
deepSplit |
integer value between 0 and 4. Provides a simplified control over how sensitive
module detection should be to module splitting, with 0 least and 4 most sensitive. See
|
networkType |
network type. Allowed values are (unique abbreviations of) |
TOMType |
one of |
corFnc |
character string specifying the function to be used to calculate co-expression similarity for correlation networks. Defaults to Pearson correlation. Any function returning values between -1 and 1 can be used. |
mergeCutHeight |
dendrogram cut height for module merging. |
sft_RsquaredCut |
desired minimum scale free topology fitting index R^2. Default is 0.80. |
reassignThreshold |
p-value ratio threshold for reassigning genes between modules. See Details. |
maxBlockSize |
integer giving maximum block size for module detection. Ignored if |
Returns a lists containing network input parameters used for WGCNA, WGCNA module information, and quality control plots.
This is a wrapper for WGCNA.
sample_dat_dir<-system.file("extdata", "sample_dat.Rdata", package = "GmicR", mustWork = TRUE) load(sample_dat_dir) # GMIC_Builder<-Auto_WGCNA(sample_dat, mergeCutHeight = 0.35, # minModuleSize = 10)