Description Usage Arguments Value Examples
Module-trait heatmap
1 2 3 4 5 6 7 8 9 10 11 |
MEs_col |
Module epigenes generated in |
traitData |
Sample attributes data frame.
Or the "traitData" generated in |
corType |
character string specifying the correlation to be used. Allowed values are (unique
abbreviations of) |
saveplot |
Save plot to given file "a.pdf", "b.png". |
prefix |
prefix for output files. |
angle_x |
Rotation angle for x-axis labels |
up_color |
Vector of colours to use for upper triangles (which representing pearson correlations values). |
down_color |
Vector of colours to use for lower triangles (which representing significance p-values). |
... |
Additional parameters given to plot output ( |
A dataframe.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | 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)
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