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

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/plot.pigengene.R

Description

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

Usage

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## 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

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     ## 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.