Loop through columns to generate PCA from DESeq2 data-CodePudding

I'd like to generate a PCA of my bulk RNAseq data, coloured by each of my variables in the DESeq2 object "vsd". My current code looks like this (to generate a single plot):

pcaData <- plotPCA(vsd, intgroup=c("Age", "BlastRate"), returnData=TRUE)
percentVar <- round(100 * attr(pcaData, "percentVar"))
ggplot(pcaData, aes(PC1, PC2, color=Age, shape=BlastRate))  
  geom_point(size=3)  
  xlab(paste0("PC1: ",percentVar[1],"% variance"))  
  ylab(paste0("PC2: ",percentVar[2],"% variance"))  
  geom_text(aes(label=name),hjust=-.2, vjust=0)  
  ggtitle("Principal Component Analysis")

Can anyone suggest a method to loop through and swap "Age" with the other variable columns of vsd?

>head(colData(vsd),1)
DataFrame with 1 row and 14 columns
        LibSize LibDiversity PercMapped      Age SpermStatus   SpConc    SpMot Subject.Group PairedSample FertRate
       <factor>     <factor>   <factor> <factor> <character> <factor> <factor>      <factor>     <factor> <factor>
sRNA_1      Low         High       High    42-46         unk      unk      unk     Male-Male            2      Low
       BlastRate RNABatch LibPrepBatch sizeFactor
        <factor> <factor>     <factor>  <numeric>
sRNA_1       Low        1            6   0.929408

CodePudding user response：

Let's mock up some data, since the example you provide is too short and ill-formatted to do anything with. I'm assuming you have data of roughly the following structure:

library(ggplot2)
library(DESeq2)

dds <- makeExampleDESeqDataSet()
colData(dds) <- cbind(colData(dds), age = runif(ncol(dds), max = 50))

dds <- DESeq(dds)
vsd <- vst(dds, nsub = 200) # 200 is for example purposes

pcaData <- plotPCA(vsd, returnData = TRUE)

Next, we can select the column-names that you want to illustrate as a vector of strings and loop through them. You can use the .data pronoun to subset a particular column when using tidyverse-style non-standard evaluation.

vars <- tail(colnames(pcaData), 2)

plot_list <- lapply(vars, function(myvar) {
  
  ggplot(pcaData, aes(PC1, PC2, colour = .data[[myvar]]))  
    geom_point()
  
})

# Just to show that there are multiple plots
patchwork::wrap_plots(plot_list)

^{Created on 2022-03-09 by the reprex package (v2.0.1)}