用ggplot facet_wrap覆盖R中的不同vline

Question

我正试图制作一组密度图，显示四种细胞类型中两组基因表达水平分布的差异。除了密度图之外，我还希望将两组的中值表达水平叠加到每个图上。根据对几个类似问题的回答，我已经能够得到正确的情节或正确的媒介，但不能同时得到两者。我没有什么想法，希望有人能纠正我。谢谢

此处提供示例数据：https://github.com/adadiehl/sample_data/blob/master/sample.data

第一次尝试。生成正确的图，但在所有四个上都绘制了相同的中间值：

dat = read.table("sample.data")
g = ggplot(dat[which(dat$FPKM > 0),], aes(x = FPKM))
g = g + geom_density(aes(y = ..density.., group = class, color = class, fill = class), alpha=0.2)
g = g + geom_vline(data=dat, aes(xintercept = median(dat$FPKM[ which(dat$FPKM > 0 & dat$class == "Other") ]) ), colour="turquoise3", linetype="longdash")
g = g + geom_vline(data=dat, aes(xintercept = median(dat$FPKM[ which(dat$FPKM > 0 & dat$class == "a_MCKG") ]) ), colour="tomato1", linetype="longdash")
g = g + facet_wrap(~source, ncol=2, scales="free")
g = g + ggtitle("Distribution of FPKM, MCKG vs. Other")
g = g + xlab("FPKM > 0")

第二次尝试：正确的绘图，但在所有绘图上放置所有中间分隔符：

dat = read.table("sample.data")
vline.dat = data.frame(z=levels(dat$source), vl=tapply(dat$FPKM[which(dat$class != "a_MCKG" & dat$FPKM > 0)], dat$source[which(dat$class != "a_MCKG" & dat$FPKM > 0)], median), vm=tapply(dat$FPKM[which(dat$class == "a_MCKG" & dat$FPKM > 0)], dat$source[which(dat$class == "a_MCKG" & dat$FPKM > 0)], median))
g = ggplot(dat[which(dat$FPKM > 0),], aes(x = FPKM))
g = g + geom_density(aes(y = ..density.., group = class, color = class, fill = class), alpha=0.2)
g = g + facet_wrap(~source, ncol=2, scales="free")
g = g + geom_vline(data=vline.dat, aes(xintercept = vl), colour="turquoise3", linetype="longdash")
g = g + geom_vline(data=vline.dat, aes(xintercept = vm), colour="tomato1", linetype="longdash")
g = g + facet_wrap(~source, ncol=2, scales="free")
g = g + ggtitle("Distribution of FPKM, MCKG vs. Other")
g = g + xlab("FPKM > 0")

第三次尝试：图都是一样的，但中间带正确。

dat = read.table("sample.data")
vline.dat = data.frame(z=levels(dat$source), vl=tapply(dat$FPKM[which(dat$class != "a_MCKG" & dat$FPKM > 0)], dat$source[which(dat$class != "a_MCKG" & dat$FPKM > 0)], median), vm=tapply(dat$FPKM[which(dat$class == "a_MCKG" & dat$FPKM > 0)], dat$source[which(dat$class == "a_MCKG" & dat$FPKM > 0)], median))
g = ggplot(dat[which(dat$FPKM > 0),], aes(x = FPKM))
g = g + geom_density(aes(y = ..density.., group = class, color = class, fill = class), alpha=0.2)
g = g + facet_wrap(~source, ncol=2, scales="free")
g = g + geom_vline(data=vline.dat, aes(xintercept = vl), colour="turquoise3", linetype="longdash")
g = g + geom_vline(data=vline.dat, aes(xintercept = vm), colour="tomato1", linetype="longdash")
g = g + facet_wrap(~z, ncol=2, scales="free")
g = g + ggtitle("Distribution of FPKM, MCKG vs. Other")
g = g + xlab("FPKM > 0")

Answer 1

传递预先汇总的数据是一种方法：

library(plyr)
names(dat) <- c("FPKM", "class", "source")
dat2 <- subset(dat, FPKM > 0)
ggplot(dat2, aes(x = FPKM)) + 
  geom_density(aes(y = ..density.., group = class, color = class, fill = class), alpha=0.2) +
  geom_vline(data = ddply(dat2, .(source, class), summarize, mmed = median(FPKM)),
             aes(xintercept = mmed, color = class)) +
  facet_wrap(~ source, ncol = 2, scales = "free") +
  ggtitle("Distribution of FPKM, MCKG vs. Other") +
  xlab("FPKM > 0")

或者，您可以使用基本R:实现相同的功能

dat3 <- aggregate(FPKM ~ source + class, data = dat2, FUN = median)
ggplot(dat2, aes(x = FPKM)) + 
  geom_density(aes(y = ..density.., group = class, color = class, fill = class), alpha=0.2) +
  geom_vline(data = dat3,
             aes(xintercept = FPKM, color = class)) +
  facet_wrap(~ source, ncol = 2, scales = "free") +
  ggtitle("Distribution of FPKM, MCKG vs. Other") +
  xlab("FPKM > 0")

注意：您可能需要避免使用source和class等列名，因为它们与内置函数冲突