R:如何绘制热图除以对角线?

问题描述

我在《自然方法》中遇到了这篇文章，该文章提供了一个非常好的热图: http://www.nature.com/nmeth/journal/v12/n4/full/nmeth.3311.html

与其他热图不同的是，每个矩形均由对角线分隔，其中一部分代表文献数据，另一部分代表内部数据.我认为这是比较数据的一种非常好的方法.但是，我不知道如何在R中绘制这张照片.有人对此有任何线索吗?

下面提供了一个小屏幕截图:

下面是2 * 2网格的演示数据集.我想要按组划分的四个矩形的颜色.

  Para1 Para2值组A D 0.2 A1A E 0.4 A1B D 0.56 A1B E 0.32 A1A D 0.7 B1A E 0.16 B1B D 0.12 B1B E 0.71 B1 

解决方案

在 heatmap 或 lattice :: levelplot 中，我看不到任何精美的东西.也许有人知道 ggplot 中的方式.

这是蛮力的概念证明:

  d = data.frame(p1 = rep(LETTERS [1:2]，times = 2，each = 2)，p2 = rep(LETTERS [4:5]，times = 4)，值= c(.2，.4，.56，.32，.7，.16，.12，.71)，group = rep(c("A1"，"B1")，each = 4))x = as.numeric(d $ p1)y = as.numeric(d $ p2)plot(1，xlim = c(1，length(unique(x))+ 1)，ylim = c(1，length(unique(y))+ 1)，type ="n"，bty ="n"，xaxt ="n"，yaxt ="n"，xlab ="，ylab =")for(i in 1:nrow(d)){if(d $ group [i] =="A1")多边形(x [i] + c(0,1,1)，y [i] + c(0,0,1)，col =灰色(d $值[i]))if(d $ group [i] =="B1")多边形(x [i] + c(0,1,0)，y [i] + c(0,1,1)，col =灰色(d $值[i]))}axis(1，at = sort(unique(x))+.5，labels = levels(d $ p1)，lty = 0)axis(2，at = sort(unique(y))+.5，labels = levels(d $ p2)，lty = 0) 

您可能想要添加一个色阶，并使用比我的 value 映射到 gray 的阴影更鲜艳的颜色(值越暗)./p>

I came across this article on Nature Methods which provided a very nice heatmap:http://www.nature.com/nmeth/journal/v12/n4/full/nmeth.3311.html

Different from other heat map is each rectangle is divided by a diagonal line, with 1 part represent the literature data and the other in-house data. I think this is a very nice way to compare the data. However, I do not know how to draw this pic in R. Does anyone have any clue on how to do this?

A small screenshot is provided below:

Below is a demo dataset of a 2*2 grid. I would like the colour of the four rectagles divided by Group.

Para1  Para2 Value Group
 A      D      0.2   A1
 A      E      0.4   A1
 B      D      0.56  A1
 B      E      0.32  A1
 A      D      0.7   B1
 A      E      0.16  B1
 B      D      0.12  B1
 B      E      0.71  B1

解决方案

I don't see anything elegant in heatmap or lattice::levelplot. Maybe someone knows how in ggplot.

Here is a brute force proof-of-concept:

d=data.frame(p1=rep(LETTERS[1:2],times=2,each=2),
             p2=rep(LETTERS[4:5],times=4),
             value=c(.2,.4,.56,.32,.7,.16,.12,.71),
             group=rep(c("A1","B1"),each=4))

x=as.numeric(d$p1)
y=as.numeric(d$p2)

plot(1,xlim=c(1,length(unique(x))+1),ylim=c(1,length(unique(y))+1),
  type="n",bty="n",xaxt="n",yaxt="n",xlab="",ylab="")

for(i in 1:nrow(d)) {
  if(d$group[i]=="A1") polygon(x[i]+c(0,1,1),y[i]+c(0,0,1),col=gray(d$value[i]))
  if(d$group[i]=="B1") polygon(x[i]+c(0,1,0),y[i]+c(0,1,1),col=gray(d$value[i]))
}

axis(1,at=sort(unique(x))+.5,labels=levels(d$p1),lty=0)
axis(2,at=sort(unique(y))+.5,labels=levels(d$p2),lty=0)

You'd probably want to add a color scale, and use something more colorful than my mapping of value to shades of gray (lower values are darker).

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