I'm trying to use DESeq2's PCAPlot function in a meta-analysis of data.

Most of the files I have received are raw counts pre-normalization. I'm then running DESeq2 to normalize them, then running PCAPlot.

One of the files I received does not have raw counts or even the FASTQ files, just the data that has already been normalized by DESeq2.

How could I go about importing this data (non-integers) as a DESeqDataSet object after it has already been normalized?

Consensus in vignettes and other comments seems to be that objects can only be constructed from matrices of integers.

I was mostly concerned with getting the format the same between plots. Ultimately, I just used a workaround to get the plots looking the same via ggfortify.

If anyone is curious, I just ended up doing this. Note, the "names" file is just organized like the meta file for colData for building a DESeq object from DESeqDataSetFrom Matrix, but I changed the name of the design column from "conditions" to "group" so it would match the output of PCAplot. Should look identical.

library(ggfortify)

data<-read.csv('COUNTS.csv',sep = ",", header = TRUE, row.names = 1)

names<-read.csv("NAMES.csv")

PCA<-prcomp(t(data))

autoplot(PCA, data = names, colour = "group", size=3)