mrbin (version 1.9.1)

mrheatmap: A function for plotting heatmaps.

Description

This function plots heatmaps based on rank order, using heatmap from the stats package

Usage

mrheatmap(
  results,
  binlist = NULL,
  samplelist = NULL,
  annotate = FALSE,
  cexRow = 0.7,
  cexCol = 0.8,
  margins = c(4, 6),
  Colv = NA,
  Rowv = NULL,
  closeDevice = TRUE,
  ...
)

Value

None

Arguments

results

Either an mrbin object or a numeric matrix containing sample names as rownames and feature names as columns names.

binlist

A vector containing bin names as they are generated by mrbin (colnames). If provided, only these columns will be shown.

samplelist

A vector containing sample names (rownames). If provided, only these rows will be shown.

annotate

Should peak annotations be shown? This requires annotation data in the mrbin object.

cexRow

Font size for row labels

cexCol

Font size for column labels

margins

Determines the plot margins.

Colv

Determines if and how the column dendrogram should be computed and reordered. Default: NA (dendrogram will not be used)

Rowv

Determines if and how the row dendrogram should be computed and reordered. Default: NULL (dendrogram will be used)

closeDevice

Should previous plots be closed prior to plotting?

...

Additional graphical parameters that will be passed to the stats function heatmap

Examples

resetEnv()
# First create NMR bin data, then plot some differential bins.
results<-mrbin(silent=TRUE,setDefault=TRUE,parameters=list(verbose=FALSE,
                dimension="1D",binwidth1D=0.01,PCA="No",showSpectrumPreview="No",
                signal_to_noise1D=25,noiseThreshold=0.75,useAsNames="Spectrum titles",
                NMRfolders=c(
                system.file("extdata/1/10/pdata/10",package="mrbin"),
                system.file("extdata/2/10/pdata/10",package="mrbin"),
                system.file("extdata/3/10/pdata/10",package="mrbin"))
                ))
metadata<-c(0,0,1)
#Find significant signals
pvalues<-rep(NA,ncol(results$bins))
names(pvalues)<-colnames(results$bins)
for(i in 1:ncol(results$bins)){
	model<-stats::lm(intensity~treatment, 
     data=data.frame(intensity=results$bins[,i],treatment=metadata))
	pvalues[i]<-stats::anova(model)$"Pr(>F)"[1]
}
significantBins<-names(sort(pvalues)[1:30]) 
metaboliteIdentities=matrix(c(1.346,1.324,21,23,
                              4.12,4.1,70.8578,71.653,
                              3.052,3.043,30.5,33.5,
                              4.066,4.059,57,59.5,
                              5.7,6.0,0,150),
                   ncol=4,byrow=TRUE)
#Annotate the dataset with signal identities
rownames(metaboliteIdentities)=c("Lactate","Lactate","Creatinine","Creatinine","Urea")
results<-annotatemrbin(results,metaboliteIdentities=metaboliteIdentities)
mrheatmap(results=results,
    binlist=significantBins,annotate=TRUE,
    main="Significant signals")