R: Centering heatmap.2 key (gplots package)

heatmapr

I would like to create a heatmap via the heatmap.2() command with a color key that is centered on 0 (i.e. white color -> 0, red -> greater than 0, blue -> less than 0) while keeping scale="none" as I am interested in plotting a heatmap of the actual values. However, all of my heatmaps are not centered on zero upon using the following line:

library(gplots)
outputHeatmap <- heatmap.2(heatmapInputActual, dendrogram="none", Rowv=FALSE,
    Colv=FALSE, col= bluered(256), scale="none", key=TRUE, density.info="none", 
    trace="none", cexRow=0.125, cexCol=0.125, symm=FALSE, symkey=TRUE)

I thought that using the command symkey=TRUE would work, but it does not. The variable I am trying make a heatmap of is an (n x 3) matrix of numerical values. A problematic input to the heatmap.2() command described above follows:

8.408458  5.661144   0.00000000
4.620846  4.932283  -0.46570468
-4.638912 -3.471838  -0.12146109
-4.822829 -3.946024   0.06403327
3.948832  4.520447  -0.31945941

Thank you for your time. I look forward to your replies.

Best Answer

The solution seem to be just adding symbreaks to your heatmap.2. Here is a fully reproducible example with your data:

library(gplots)
#read your example data
heatmapInputActual <- read.table(textConnection(
"8.408458 5.661144 0.00000000
4.620846 4.932283 -0.46570468
-4.638912 -3.471838 -0.12146109
-4.822829 -3.946024 0.06403327
3.948832 4.520447 -0.31945941
"),as.is=TRUE)
#convert sample data to matrix
heatmapInputActual <- as.matrix(heatmapInputActual)
#just add symbreaks to the end of your code
heatmap.2(heatmapInputActual, dendrogram="none", Rowv=FALSE, Colv=FALSE, 
          col = bluered(256), scale="none", key=TRUE, density.info="none", 
          trace="none", cexRow=0.125, cexCol=0.125, symm=F,symkey=T,symbreaks=T)

enter image description here

Related Solutions

R – Heatmap of Microarray Data using Pearson Distance

Ok...I think you are simply confused about how cor and dist operate. From the documentation on dist:

This function computes and returns the distance matrix computed by using the specified 
    distance measure to compute the distances between the rows of a data matrix.

And from the documentation on cor:

If x and y are matrices then the covariances (or correlations) 
    between the columns of x and the columns of y are computed.

See the difference? dist (and dist objects, which is what heatmap.2 is assuming it's getting) assume that you've calculated the distance between rows, while using cor you are essentially calculating the distance between columns. Adding a simple transpose to your distance function allows this (non-square) example to run for me:

TEST <- matrix(runif(100),nrow=20)
heatmap.2(t(TEST), trace="none", density="none", 
            scale="row",
            labRow="",
            hclust=function(x) hclust(x,method="complete"),
            distfun=function(x) as.dist((1-cor(t(x)))/2))

R- how to edit elements on x axis in image.plot

Here is a better-ish solution:

 par(mar=c(5,4.5,4,7))
 image(sample, col=rainbow(25), axes=F)  #redblue() doesn't work on my computer.
 axis(2)
 axis(1, at=seq(0,0.8,0.2), labels=rownames(sample))
 image.plot(sample, legend.only=T)

enter image description here

EDIT: Does the plot below look like what you are looking for?

 sample = cor(matrix(rnorm(400), nrow=20))
 image(cor(matrix(rnorm(400), nrow=20)), axes=F)
 mtext(text=c(paste("country",1:21)), side=2, line=0.3, at=seq(0,1,0.05), las=1, cex=0.8)
 mtext(text=c(paste("country",1:21)), side=1, line=0.3, at=seq(0,1,0.05), las=2, cex=0.8)
 image.plot(sample, legend.only=T)

enter image description here

Best Answer

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R – Heatmap of Microarray Data using Pearson Distance

R- how to edit elements on x axis in image.plot

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