Hi there,

I am having trouble figuring out how to subset my data to look at gene expression within particular groups. I have 38 samples with two factors - temperature with 2 levels (28 and 36), and stage with 3 levels (s1, s2, and s3). While I can readily contrast within each factor

res <- results(dds, contrast=c("stage","s1","s3"), alpha=0.05, lfcThreshold=1) res <- results(dds, contrast=c("temp","28","36"), alpha=0.05, lfcThreshold=1)

I want to be able to look at genes that are differentially expressed between the two temperatures within each stage. I have tried creating a new factor containing only values for a single stage stage3 <- factor(c( "s3", "s3", "s3", "s3", "s3", "s3", "s3","s3" ,"s3","s3" , "s3","s3","s3","s3"))

test <- results(dds, contrast=c("stage3","28","36"), alpha=0.05, lfcThreshold=1)

And get an error message that 28 and 36 should be levels of stage 3, which of course indicates that the way I'm trying to set this up is fundamentally wrong.

Any suggestions would be greatly appreciated!

Session info R version 3.5.3 (2019-03-11) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 17134)

Check out the vignette section on interactions, we have example code of how to combine two factors into one so that you can make these comparisons.

It's a little hard to find in the vignette, but you want to do this:

dds$group <- factor(paste0(dds$genotype, dds$condition))
design(dds) <- ~ group
dds <- DESeq(dds)
resultsNames(dds)
results(dds, contrast=c("group", "IB", "IA"))

This is how you compare one subset of samples to another subset of samples