Auto_WGCNA: Carries out WGCNA with default settings or custom settings

In GmicR: Combines WGCNA and xCell readouts with bayesian network learrning to generate a Gene-Module Immune-Cell network (GMIC)

Description

Carries out WGCNA with default settings or custom settings

Usage

Auto_WGCNA(
  datExpr,
  colname_correct = TRUE,
  minModuleSize = 10,
  deepSplit = 4,
  networkType = "signed hybrid",
  TOMType = "unsigned",
  corFnc = "bicor",
  mergeCutHeight = 0.25,
  sft_RsquaredCut = 0.85,
  removeFirst = FALSE,
  reassignThreshold = 1e-06,
  maxBlockSize = 25000,
  nThreads = NULL
)

Arguments

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 checkMissingData below and details.
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 cutreeDynamic for more details.
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 cutreeDynamic for more details.
networkType	network type. Allowed values are (unique abbreviations of) "unsigned", "signed", "signed hybrid". See adjacency.
TOMType	one of "none", "unsigned", "signed". If "none", adjacency will be used for clustering. If "unsigned", the standard TOM will be used (more generally, TOM function will receive the adjacency as input). If "signed", TOM will keep track of the sign of correlations between neighbors.
corFnc	the correlation function to be used in adjacency calculation.
mergeCutHeight	dendrogram cut height for module merging.
sft_RsquaredCut	desired minimum scale free topology fitting index R^2. Default is 0.80.
removeFirst	should the first bin be removed from the connectivity histogram?
reassignThreshold	p-value ratio threshold for reassigning genes between modules. See Details.
maxBlockSize	integer giving maximum block size for module detection. Ignored if blocks above is non-NULL. Otherwise, if the number of genes in datExpr exceeds maxBlockSize, genes will be pre-clustered into blocks whose size should not exceed maxBlockSize.
nThreads	non-negative integer specifying the number of parallel threads to be used by certain parts of correlation calculations. This option only has an effect on systems on which a POSIX thread library is available (which currently includes Linux and Mac OSX, but excludes Windows). If zero, the number of online processors will be used if it can be determined dynamically, otherwise correlation calculations will use 2 threads.

Value

Returns a lists containing network input parameters used for WGCNA, WGCNA module information, and quality control plots.

Note

This is a wrapper for WGCNA.

See Also

blockwiseModules

adjacency

Examples

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)

GmicR documentation built on Nov. 8, 2020, 7:07 p.m.