PAA (version 1.7.1)

plotFeaturesHeatmap.2: Alternative function to plot feature intensities as a heatmap.

Description

This function is an alternative to plotFeaturesHeatmap() and is based on the function heatmap.2() provided by the package gplots.

Usage

plotFeaturesHeatmap.2(features = NULL, elist = NULL, n1 = NULL, n2 = NULL,  output.path = NULL, description=FALSE)

Arguments

features

vector containing the selected features as "BRC"-IDs (mandatory).

elist

EListRaw or EList object containing all intensity data in log2 scale (mandatory).

n1

integer indicating the sample size of group 1 (mandatory).

n2

integer indicating the sample size of group 2 (mandatory).

output.path

path for saving the heatmap as a png file (default: NULL).

description

if TRUE, features will be described via protein names instead of UniProtKB accessions (default: FALSE).

Value

No value is returned.

Details

Plots intensities of all features given in the vector features via their corresponding "BRC"-IDs as a heatmap. If description is TRUE (default: FALSE), features will be described via protein names instead of UniProtKB accessions. Furthermore, if output.path is not NULL, the heatmap will be saved as a png file in output.path. This function can be used to check whether the selected features are differential.

plotFeaturesHeatmap.2() is an alternative to plotFeaturesHeatmap() and is based on the function heatmap.2() provided by the package gplots.

References

The package gplots by Gregory R. Warnes et al. can be downloaded from CRAN (http://CRAN.R-project.org/package=gplots).

Gregory R. Warnes, Ben Bolker, Lodewijk Bonebakker, Robert Gentleman, Wolfgang Huber, Andy Liaw, Thomas Lumley, Martin Maechler, Arni Magnusson, Steffen Moeller, Marc Schwartz and Bill Venables (2015). gplots: Various R Programming Tools for Plotting Data. R package version 2.17.0. http://CRAN.R-project.org/package=gplots

Examples

cwd <- system.file(package="PAA")
load(paste(cwd, "/extdata/Alzheimer.RData", sep=""))
#elist <- elist[elist$genes$Block < 10,]

#c1 <- paste(rep("AD",20), 1:20, sep="")
#c2 <- paste(rep("NDC",20), 1:20, sep="")

#pre.sel.results <- preselect(elist=elist, columns1=c1, columns2=c2, label1="AD",
# label2="NDC", discard.threshold=0.1, fold.thresh=1.9, discard.features=TRUE,
# method="tTest")
#elist <- elist[-pre.sel.results$discard,]

#selectFeatures.results <- selectFeatures(elist,n1=20,n2=20,label1="AD",
# label2="NDC",selection.method="rf.rfe",preselection.method="none",subruns=2,
# k=2,candidate.number=20,method="frequency")
 
load(paste(cwd, "/extdata/selectFeaturesResultsFreq.RData", sep="")) 
plotFeaturesHeatmap.2(features=selectFeatures.results$features, elist=elist,
 n1=20, n2=20, description=TRUE)