User:Timothee Flutre/Notebook/Postdoc/2011/11/09: Difference between revisions
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(→Entry title: replace rownames with mapping when different order) |
(→Entry title: add custom heatmap) |
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new.rownames <- unlist(lapply(rownames(mat), function(i){links$id2[which(links$id1 == i)]})) | new.rownames <- unlist(lapply(rownames(mat), function(i){links$id2[which(links$id1 == i)]})) | ||
rownames(mat) <- new.rownames | rownames(mat) <- new.rownames | ||
Or it's maybe easier with the built-in [http://stat.ethz.ch/R-manual/R-patched/library/base/html/match.html match] function: | |||
new.rownames <- links$id2[ match(rownames(mat), links$id1) ] | |||
* in R, visualize the missing values (encoded as "NA") in a matrix: | |||
image(1:nrow(mat), 1:ncol(mat), is.na(mat), col=c("white","black"), | |||
main="Missing values", xlab="Genes", ylab="Samples") | |||
[[Image:Visualize_missing_values_in_matrix.png|400px]] | |||
* in R, customize the built-in heatmap (inspired from [http://stackoverflow.com/questions/5687891/r-how-do-i-display-clustered-matrix-heatmap-similar-color-patterns-are-grouped/5694349 this]): | |||
S <- 3 # nb of subgroups | |||
V <- 7 # nb of observations | |||
z <- matrix(c(0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,0,0), nrow=V, ncol=S, byrow=TRUE) | |||
myheatmap <- function(z, out.file="") { | |||
def.par <- par(no.readonly=TRUE) | |||
par(mar=c(4,5,3,2), font=2, font.axis=2, font.lab=2, cex=1.5, lwd=2) | |||
if (out.file != "") | |||
pdf(out.file) | |||
layout(mat=cbind(1, 2), width=c(7,1)) # plot + legend | |||
mycol <- rev(heat.colors(4)) | |||
image(x=1:NCOL(z), y=1:NROW(z), z=t(z), | |||
xlim=0.5+c(0,NCOL(z)), ylim=0.5+c(0,NROW(z)), | |||
xlab="", ylab="Observations sorted by cluster", main="Custom heatmap", | |||
axes=FALSE, col=mycol) | |||
axis(1, 1:NCOL(z), labels=paste("subgroup", 1:NCOL(z)), tick=0) | |||
par(mar=c(0,0,0,0)) | |||
plot.new() | |||
legend("center", legend=sprintf("%.2f", seq(from=min(z), to=max(z), length.out=5)[-1]), | |||
fill=mycol, border=mycol, bty="n") | |||
if (out.file != "") | |||
dev.off() | |||
par(def.par) | |||
} | |||
myheatmap(mydata.sort) | |||
<!-- ##### DO NOT edit below this line unless you know what you are doing. ##### --> | <!-- ##### DO NOT edit below this line unless you know what you are doing. ##### --> | ||
Revision as of 09:24, 22 May 2014
 Project name
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Entry title
links <- data.frame(id1=c("a","b","c"), id2=c("1","2","3"), stringsAsFactors=FALSE)
mat <- matrix(runif(3*10), nrow=3)
rownames(mat) <- c("b","c","a")
new.rownames <- unlist(lapply(rownames(mat), function(i){links$id2[which(links$id1 == i)]}))
rownames(mat) <- new.rownames
Or it's maybe easier with the built-in match function: new.rownames <- links$id2[ match(rownames(mat), links$id1) ]
image(1:nrow(mat), 1:ncol(mat), is.na(mat), col=c("white","black"),
main="Missing values", xlab="Genes", ylab="Samples")
S <- 3 # nb of subgroups
V <- 7 # nb of observations
z <- matrix(c(0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,0,0), nrow=V, ncol=S, byrow=TRUE)
myheatmap <- function(z, out.file="") {
def.par <- par(no.readonly=TRUE)
par(mar=c(4,5,3,2), font=2, font.axis=2, font.lab=2, cex=1.5, lwd=2)
if (out.file != "")
pdf(out.file)
layout(mat=cbind(1, 2), width=c(7,1)) # plot + legend
mycol <- rev(heat.colors(4))
image(x=1:NCOL(z), y=1:NROW(z), z=t(z),
xlim=0.5+c(0,NCOL(z)), ylim=0.5+c(0,NROW(z)),
xlab="", ylab="Observations sorted by cluster", main="Custom heatmap",
axes=FALSE, col=mycol)
axis(1, 1:NCOL(z), labels=paste("subgroup", 1:NCOL(z)), tick=0)
par(mar=c(0,0,0,0))
plot.new()
legend("center", legend=sprintf("%.2f", seq(from=min(z), to=max(z), length.out=5)[-1]),
fill=mycol, border=mycol, bty="n")
if (out.file != "")
dev.off()
par(def.par)
}
myheatmap(mydata.sort)
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