Auto_WGCNA: Carries out WGCNA with default settings or custom settings

Description Usage Arguments Value Note See Also Examples

View source: R/Auto_WGCNA.R

Description

Carries out WGCNA with default settings or custom settings

Usage

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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
)

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

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 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.

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

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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 Feb. 16, 2020, 2 a.m.