WGCNA_cytoscape: Export WGCNA resullt for cytoscape input edges and nodes.

In Tong-Chen/YSX: For Yishengxin Training

Description

Export WGCNA resullt for cytoscape input edges and nodes.

Usage

WGCNA_cytoscape(
  net,
  power,
  datExpr,
  TOM_plot = NULL,
  prefix = "ehbio",
  fulledge = F
)

Arguments

net	WGCNA_coexprNetwork or blockwiseModules returned WGCNA object.
power	soft-thresholding power for network construction.
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.
TOM_plot	Get TOM plot and save to file given here like 'tomplot.pdf'.
prefix	prefix for output files.
fulledge	Output all edges (very large). Default FALSE. Only output edges whithin modules.

Value

A list with edgeData and nodeData as two elements.

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)

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

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

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