plot.pigengene: Plots and saves a 'pigengene' object

In Pigengene: Infers biological signatures from gene expression data

Description

Plots a couple of heatmaps of expression of the eigengenes, weights (memberships), and so on. Saves the plots in png format.

Usage

## S3 method for class 'pigengene'
plot(x, saveDir = NULL, 
  DiseaseColors="Auto", 
  fontsize = 35, doShowColnames = TRUE, fontsizeCol = 25, 
  doClusterCols = ncol(pigengene$eigengenes) > 1, 
  verbose = 2, doShowRownames = "Auto", 
  pngfactor = max(2, ncol(pigengene$eigengenes)/16), do0Mem = FALSE, ...)

Arguments

x	The object from pigengene-class computed by compute.pigengene.
saveDir	The dirctory for saving the plots
DiseaseColors	A vector of characters determining color for each disease. Names should match the values in the first column of x$annotation.
fontsize	Passd to pheatmap.type
doShowColnames	Boolean
fontsizeCol	Numeric
doClusterCols	Boolean
verbose	The integer level of verbosity. 0 means silent and higher values produce more details of computation.
doShowRownames	Boolean
pngfactor	A numeric adjusting the size of the png files
do0Mem	If TRUE, module 0 genes are included in the membership heatmap.
...	Passd to pheatmap.type function

Details

Many of the arguments are passed to pheatmap.

Value

A list of:

heat	The full output of pheatmap functionion
heatNotRows	The full output of pheatmap.type function

Author(s)

Habil Zare ad Amir Foroushani

References

Large-scale gene network analysis reveals the significance of extracellular matrix pathway and homeobox genes in acute myeloid leukemia, Foroushani A, Agrahari R, Docking R, Karsan A, and Zare H. In preparation.

See Also

Pigengene-package, compute.pigengene, pheatmap.type

Examples

     ## Data:
     data(aml)
     data(mds)
     data(eigengenes33)
     d1 <- rbind(aml,mds)
     Labels <- c(rep("AML",nrow(aml)),rep("MDS",nrow(mds)))
     names(Labels) <- rownames(d1)
     Labels <- c(rep("AML",nrow(eigengenes33$aml)),rep("MDS",nrow(eigengenes33$mds)))
     names(Labels) <- rownames(d1)
     toyModules <- eigengenes33$modules[colnames(d1)]
     ## Computing:
     p1 <- compute.pigengene(Data=d1, Labels=Labels, modules=toyModules, 
        saveFile="pigengene.RData", doPlot=TRUE, verbose=3)
     plot(p1,saveDir="plots")

Pigengene documentation built on Nov. 8, 2020, 6:47 p.m.