WGCNA_GeneModuleTraitCoorelation: Genes correlated with both traits an modules.

In Tong-Chen/YSX: For Yishengxin Training

Description

Genes correlated with both traits an modules.

Usage

WGCNA_GeneModuleTraitCoorelation(
  datExpr,
  MEs_col,
  geneTraitCor,
  traitData,
  net,
  corType = "bicor",
  prefix = "ehbio",
  ...
)

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.
MEs_col	Module epigenes generated in WGCNA_saveModuleAndMe.
geneTraitCor	A dataframe generated by WGCNA_ModuleGeneTraitHeatmap
traitData	Sample attributes data frame. Or the "traitData" generated in WGCNA_readindata.
net	WGCNA_coexprNetwork or blockwiseModules returned WGCNA object.
corType	character string specifying the correlation to be used. Allowed values are (unique abbreviations of) "pearson" and "bicor", corresponding to Pearson and bidweight midcorrelation, respectively. Missing values are handled using the pairwise.complete.obs option.
prefix	prefix for output files.
...	Additional parameters given to plot output (pdf, png,...) like "width", "height", .etc.

Examples

df = generateAbundanceDF(nSample=30, nGrp=3, sd=5)
datExpr <- WGCNA_dataFilter(df)
datExpr <- WGCNA_sampleClusterDetectOutlier(datExpr)
power <- WGCNA_softpower(datExpr)
net <- WGCNA_coexprNetwork(datExpr, power)
WGCNA_saveModuleAndMe(net, datExpr)
cyt <- WGCNA_cytoscape(net, power, datExpr)
hubgene <- WGCNA_hubgene(cyt)

#2
exprMat <- "test.file"
wgcnaL <- WGCNA_readindata(exprMat)

traitData <- 'trait.file'
wgcnaL <- WGCNA_readindata(exprMat, traitData)
datExpr <- wgcnaL$datExpr
traitData <- wgcnaL$traitData
WGCNA_dataCheck(datExpr)
datExpr <- WGCNA_dataFilter(datExpr)
datExpr <- WGCNA_sampleClusterDetectOutlier(datExpr)
# datExpr <- WGCNA_sampleClusterDetectOutlier(datExpr, traitColors=wgcnaL$traitColors)
power <- WGCNA_softpower(datExpr)
net <- WGCNA_coexprNetwork(datExpr, power)
MEs_col <- WGCNA_saveModuleAndMe(net, datExpr)
WGCNA_MEs_traitCorrelationHeatmap(MEs_col, traitData=traitData)
cyt <- WGCNA_cytoscape(net, power, datExpr)
hubgene <- WGCNA_hubgene(cyt)
WGCNA_moduleTraitPlot(MEs_col, traitData=traitData)
geneTraitCor <- WGCNA_ModuleGeneTraitHeatmap(datExpr, traitData, net)
WGCNA_GeneModuleTraitCoorelation(datExpr, MEs_col, geneTraitCor, traitData, net)

Tong-Chen/YSX documentation built on Jan. 25, 2021, 2:49 a.m.