画热点图的办法 R语言包gplots

moshengren

用gplots包中的heatmap.2函数就可以画出想要的热图heatmap
下面举一个例子，作为演示，大家就会知道怎么画这种图。
当然，需求样式，还得根据heatmap.2中的参数自己调整

生物统计家园 heatmap图例子

library(gplots)
data(mtcars)
x  <- as.matrix(mtcars)
rc <- rainbow(nrow(x), start=0, end=.3)
cc <- rainbow(ncol(x), start=0, end=.3)

heatmap.2(x)  ## default - dendrogram plotted and reordering done.
heatmap.2(x, dendrogram="none") ##  no dendrogram plotted, but reordering done.
heatmap.2(x, dendrogram="row") ## row dendrogram plotted and row reordering done.
heatmap.2(x, dendrogram="col") ## col dendrogram plotted and col reordering done.

heatmap.2(x, keysize=2)  ## default - dendrogram plotted and reordering done.

heatmap.2(x, Rowv=FALSE, dendrogram="both") ## generate warning!
heatmap.2(x, Rowv=NULL, dendrogram="both")  ## generate warning!
heatmap.2(x, Colv=FALSE, dendrogram="both") ## generate warning!



hv <- heatmap.2(x, col=cm.colors(256), scale="column",
               RowSideColors=rc, ColSideColors=cc, margin=c(5, 10),
               xlab="specification variables", ylab= "Car Models",
               main="heatmap(<Mtcars data>, ..., scale=\"column\")",
               tracecol="green", density="density")

str(hv) # the two re-ordering index vectors

data(attitude)
round(Ca <- cor(attitude), 2)
symnum(Ca) # simple graphic

# with reorder
heatmap.2(Ca,           symm=TRUE, margin=c(6, 6), trace="none" )

# without reorder
heatmap.2(Ca, Rowv=FALSE, symm=TRUE, margin=c(6, 6), trace="none" )

## Place the color key below the image plot
heatmap.2(x, lmat=rbind( c(0, 3), c(2,1), c(0,4) ), lhei=c(1.5, 4, 2 ) )

## Place the color key to the top right of the image plot
heatmap.2(x, lmat=rbind( c(0, 3, 4), c(2,1,0 ) ), lwid=c(1.5, 4, 2 ) )

## For variable clustering, rather use distance based on cor():
data(USJudgeRatings)
symnum( cU <- cor(USJudgeRatings) )

hU <- heatmap.2(cU, Rowv=FALSE, symm=TRUE, col=topo.colors(16),
              distfun=function(c) as.dist(1 - c), trace="none")

## The Correlation matrix with same reordering:
hM <- format(round(cU, 2))
hM

# now with the correlation matrix on the plot itself

heatmap.2(cU, Rowv=FALSE, symm=TRUE, col=rev(heat.colors(16)),
             distfun=function(c) as.dist(1 - c), trace="none",
             cellnote=hM)

## genechip data examples
## Not run:
library(affy)
data(SpikeIn)
pms <- SpikeIn@pm

# just the data, scaled across rows
heatmap.2(pms, col=rev(heat.colors(16)), main="SpikeIn@pm",
              xlab="Relative Concentration", ylab="Probeset",
              scale="row")

# fold change vs "12.50" sample
data <- pms / pms[, "12.50"]
data <- ifelse(data>1, data, -1/data)
heatmap.2(data, breaks=16, col=redgreen, tracecol="blue",
               main="SpikeIn@pm Fold Changes\nrelative to 12.50 sample",
               xlab="Relative Concentration", ylab="Probeset")
## End(Not run)