Hey, I wanted to ask for advice about some analysis I am doing. I have a count matrix (raw) and a metadata dataframe (condition_breakfast) for DESeq analysis.

dds_V_vs_L <- DESeqDataSetFromMatrix(countData=raw, 
                                     colData=condition_breakfast, 
                                     design=~ Campione)

In condition_breakfast I have multiple columns:

ID    Risposta Braccio Campione
 1 OE05  pCR      A       V       
 2 OE06  pCR      A       L       
 3 OE07  pCR      A       V       
 4 OE08  pCR      A       L       
 5 OE09  RD       B       V       
 6 OE10  RD       B       L       
 7 OE11  pCR      B       V

How I can do a comparison between sample in (pCR-V) vs sample in (RD-V)? and sample in (pCR-L) with sample in (RD-L)? So, how i can combine multiple colData? Because if I do

 dds_V_vs_L <- DESeqDataSetFromMatrix(countData=raw, 
                                     colData=condition_breakfast, 
                                     design=~ Risposta+ Campione)

I think he compare pCR-V vs pCR-L and RD-V vd RD-L, or i'm saying wrong?

The easiest is to combine columns similar to code suggested in the vignette for interactions and then make the design on that column:

https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#interactions