在一个绘图中对不同范围的数据使用多个scale_colour_gradient比例 [英] Using multiple scale_colour_gradient scales for different ranges of the data in one plot

问题描述

我对R很新，所以如果我的问题不清楚，请耐心等待。

我有一个含有5列的 data.frame protein，即;

1.protein_name，2.protein_FC，3.protein_pval，4.mRNA_FC，5.mRNA_pval和6.freq。

我想绘制一个x = log2（protein_FC），y = -log10（protein_pval）的火山图。然后将点的大小映射到频率和颜色到mRNA_FC。这一切都正常工作，这里是我已经使用的代码：

$ $ $ p $ g $ pggplot（protein [which（protein $ freq <= 0.05），]，aes（x = log2（protein_FC），
y = -log10（protein_pval），size = freq，color = mRNA_FC，
label = paste（protein_name，，，mRNA_pval）， alpha = 1/1000））+
geom_point（）+ geom_text（hjust = 0，vjust = 0，color =black，size = 2.5）+
geom_abline（截距= 1.3，斜率= 0 ）+
scale_colour_gradient（limits = c（-3,3））

一切正常直到这里。但由于实验的性质，数据在 mRNA_FC = 0 附近是相当密集的。在那里，ggplot应用的默认配色方案在区分不同点方面效果不佳。

我已经尝试过使用 low = colour1和 high =colour2。不过，我认为最好在 mRNA_FC 范围内使用多个色阶，即类似。对于 -0.2 ，从蓝到白对于 -3 ，红到白。绿色至白色 0 ，黑色至白色 0.2 。



但我还没有找到任何方法。

任何帮助将不胜感激。
干杯！

解决方案

对于这种类型的事情，您想使用 scale_gradientn 。例如：

  library（ggplot2）
 
x = seq（-0.1，0.1，len = 100 ）
y = 0:10 
 dat = expand.grid（x = x，y = y）
 
 ggplot（data = dat，aes（x = x，y = y ，fill = x））+ 
 geom_raster（）+ 
 scale_fill_gradientn（colors = c（'red'，'yellow'，'cyan'，'blue'），
 values = c -0.05，-1e-32,1e-32,0.05），
 breaks = c（-0.05，-0.005,0.005,0.05），
 rescaler = function（x，...）x， 
 oob = identity）
  

I am very new to R so please bear with me if something is not clear in my question.

I have a data.frame "protein" with 5 columns, namely;

1.protein_name, 2.protein_FC, 3.protein_pval, 4.mRNA_FC, 5.mRNA_pval and 6.freq.

I am trying to plot a volcano plot with x=log2(protein_FC), y=-log10(protein_pval). Then map the size of the dots to freq and colour to mRNA_FC. This all works fine and here is the code that I have used:

ggplot( protein [ which ( protein$freq <= 0.05 ),] , aes( x = log2( protein_FC ) ,
       y = -log10 ( protein_pval ) , size = freq , colour = mRNA_FC , 
       label = paste(protein_name,",",mRNA_pval), alpha=1/1000)) + 
  geom_point() + geom_text( hjust = 0 , vjust = 0 , colour = "black" , size = 2.5 ) + 
  geom_abline( intercept = 1.3 , slope = 0) + 
  scale_colour_gradient(limits=c(-3,3))

all is fine till here. But because of the nature of the experiment, data it is quite dense around mRNA_FC = 0. There, the default colour scheme that ggplot applies doesnt work very well in distinguishing different points.

I have tried various colour scales by using low="colour1" and high="colour2". However I think it will be best to use multiple colour scales over the ranges of mRNA_FC, i.e. something like. blue to white for -3<mRNA<-0.2, red to white for -0.2<mRNA_FC<0, green to white for 0<mRNA_FC<0.2 and black to white for 0.2<mRNA_FC<3.

But I havent found any way of doing it yet.

Any help would be appreciated. Cheers!

解决方案

For this type of thing you want to use scale_gradientn. For example:

library(ggplot2)

x = seq(-0.1, 0.1, len=100)
y = 0:10
dat = expand.grid(x=x, y=y)

ggplot(data=dat, aes(x=x, y=y, fill=x)) +
  geom_raster() +
  scale_fill_gradientn(colours=c('red', 'yellow', 'cyan', 'blue'),
    values   = c(-0.05,-1e-32,1e-32,0.05),
    breaks   = c(-0.05,-0.005,0.005,0.05),
    rescaler = function(x,...) x,
    oob      = identity)

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