用base plot 画出Zoom的效果
<h1>背景</h1><p>用base plot画出C图这种zoom in效果的图。</p>
<p><img src="https://tcapi.voiceclouds.cn:8444/uploads/2025/11/20/mi7fxas545izfnwqfyu.png" alt="" /></p>
<p>出自PMID: 26451490文章</p>
<h1>应用场景</h1>
<p>有时会遇到这样的问题：点的分布很不均匀，堆在一起的点很难标label。</p>
<p>解决办法：画整体的同时画局部，就能看清堆在一起的点了，写label也很清晰。</p>
<p>示例图用于展示多个基因在两组中各变异类型所占的百分比，用颜色表示变异类型，泡泡大小表示pvalue，泡泡所在的位置偏左上说明在IDC中占比高于ILC，反之亦然。该图不仅限于基因。</p>
<h1>环境设置</h1>
<pre><code class="language-{r}">Sys.setenv(LANGUAGE = "en") #显示英文报错信息
options(stringsAsFactors = FALSE) #禁止chr转成factor
</code></pre>
<h1>输入文件</h1>
<p>easy_input.csv，提供分组、个数及总数（用于计算百分比）、pvalue：</p>
<ul>
<li>第一列是基因名；</li>
<li>第二列是分组；</li>
<li>第3-4、5-6列分别是在ILC（横坐标）和IDC（纵坐标）里的数量和总数，后面会用这两列计算百分比；</li>
<li>最后一列是pvalue。</li>
</ul>
<p>示例数据整理自例文的Table 1. Recurrently Mutated Genes in Breast Cancer，这里只用了mutation，没加CNV，因此泡泡的位置跟原图有出入。</p>
<pre><code class="language-{r}">dat2 <- read.csv("easy_input.csv")
head(dat2)
</code></pre>
<h1>把各列数据整理成画图所需的格式</h1>
<pre><code class="language-{r}">### 用3-6列计算百分比 ###
ILC <- (dat2$n_ILC/dat2$total_ILC)*100
names(ILC) <- dat2$Gene
IDC <- (dat2$n_IDC/dat2$total_IDC)*100
names(IDC) <- dat2$Gene
### group列 ###
# 给每个group的泡泡一种颜色
# 先自定义足够多的颜色
mycol <- c("red","navy","forestgreen","black","#FB9A99","#33A02C","#E31A1C","#B15928","#6A3D9A","#CAB2D6","#A6CEE3","#1F78B4","#FDBF6F","#999999","#FF7F00")
# 不显著的定义为notsig组，画成灰色
dat2$group <- "notsig"
cols.names <- unique(dat2$group)
cols.code <- c(mycol,"grey")
names(cols.code) <- cols.names
### pvalue列 ###
# pvalue决定泡泡的大小
sizes <- -log10(dat2$pvalue)/5
sizes <- 0
names(sizes) <- dat2$Gene
</code></pre>
<h1>开始画图</h1>
<p>Zoom in的效果，也就是画一个整体，再画一个局部。</p>
<h2>画局部</h2>
<pre><code class="language-{r,">par(mfrow=c(1,2),mar = par()$mar + c(3,0,0,3)) #在底部留出图例的地方)
plot(ILC, IDC,
col = cols.code,
xlim = c(0,15), ylim=c(0,15), #画局部
pch = 16, #实心圆点
ylab = "IDC (% altered samples)",xlab="ILC (% altered samples)",
cex = sizes)
abline(a = 0, b = 1, col = "gray60", lwd = 1, lty = 5)
# 泡泡外面画白圈
points(ILC, IDC, pch = 1, col = "white", cex = sizes)
# 给百分比大于6的泡泡标上文字
# 可以根据你自己的喜好调整
up <- which(IDC > 6)
down <- which(ILC > 6)
par(xpd=TRUE) #让超出画图范围的字也能显示出来
text(ILC, IDC, names(ILC), pos=2) #Values of 1, 2, 3 and 4, respectively indicate positions below, to the left of, above and to the right of the specified coordinates.
text(ILC, IDC, names(ILC), pos=4)
# 画黄色背景
## Add an alpha value to a colour
add.alpha <- function(col, alpha=1){
if(missing(col))
stop("Please provide a vector of colours.")
apply(sapply(col, col2rgb)/255, 2,
function(x)
rgb(x, x, x, alpha=alpha))
}
gray.alpha <- add.alpha("orange", alpha=0.1)
rect(par("usr"), par("usr"), par("usr"), par("usr"), col = gray.alpha)
# 添加pathway颜色的图例
legend("bottom",
inset=c(0,-.5), #把图例画到图外
ncol = 3,
pch=16, col=cols.code, legend=cols.names, bty="n")
### 画整体 ###
#par(mar = par()$mar + c(0,0,0,3)) #在右侧留出写title的地方
plot(ILC, IDC,
col = cols.code,
xlim=c(0,70),ylim=c(0,70),
ylab="", xlab="ILC (% altered samples)",
yaxt='n', #先不画y轴
pch=16,
cex=sizes)
# 泡泡外面画白圈
points(ILC, IDC, pch=1, col = "white", cex=sizes)
axis(side = 4) #画右侧y轴
title(ylab="IDC (% altered samples)",
mgp=c(-20,1,0)) #根据具体图的大小调整，这里取-25，让title位于右侧
# 给百分比大于15的泡泡标上文字
w <- which(ILC > 15 | IDC > 15) # ILC或IDC>15
text(ILC, IDC, names(ILC), pos=3) #Values of 1, 2, 3 and 4, respectively indicate positions below, to the left of, above and to the right of the specified coordinates.
# 添加size的图例
u <- par("usr")
f <- c(1,2.5,5,10,20)
s <- sqrt(f/3)
legend("bottom",
inset=c(0,-.5), #把图例画到图外
legend=rep("", length(f)),
title = "Significance level [-log10(q)]",
pch=1, pt.cex=s, bty='n',
horiz = TRUE, #横向排列
col="#88888888")
par(xpd = F) #默认就是F，前面为了写label改成TRUE了。画abline前一定改为FALSE，否则对角线的虚线会超出plot region
abline(a = 0, b = 1, col = "gray60", lwd = 1, lty=2)
# 给局部区域画黄色背景
# 此处的4.6是由70/15得到的
rect(par("usr")/4.6, par("usr")/4.6, par("usr")/4.6, par("usr")/4.6, col = gray.alpha, border=TRUE)
recordedplot1 <- recordPlot() # record the previous plot
pdf("baseZoom.pdf",10,5.5)
recordedplot1
dev.off()
</code></pre>
<p><img src="https://tcapi.voiceclouds.cn:8444/uploads/2025/11/20/mi7g1977abxvxty85wi.png" alt="" /></p>
<p>文中所用数据可以关注公众号“生信喵实验柴”<br />
<img src="https://tcapi.voiceclouds.cn:8444/uploads/2025/09/07/mf9nu72s90ofyseu9hl.png" alt="" /><br />
发送关键词“20250506”获取</p>
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