I am trying to use DEseq2 to determine diff. expressed genes between various conditions, but find it very difficult how to specify what I want to compare.

My experimental design has three factor columns:

• two different locations
• four different conditions
• either two or three replicates - the replicates are matched

Here is what it looks like:

I want to know which genes are diff. expressed in various combinations, f.e.:

• nucleus & ctrl vs nucleus & treatmentA
• nucleus & ctrl vs nucleus & treatmentB
• nucleus & ctrl vs cytoplasm & treatmentA
• all nucleus vs all cytoplasm

What I tried:

mycountdata <- read.delim("table.csv", header = TRUE, sep = "\t")
mycoldata <- read.delim("desc.csv", header = TRUE, sep = "\t")
dds <- DESeqDataSetFromMatrix(countData = mycountdata, colData = mycoldata, design = ~ replicate + location + condition)
dds <- DESeq(dds)

This is where I am stuck. I now want to use the results function, but I do not understand how to articulate, f.e., "compare ctrl vs treatmentA only in nucleus", "compare ctrl, nucleus vs ctrl, cytoplasm", "compare all nucleus vs all cytoplasm etc).

I think I understand what to do if I have only two factor-columns, but now that I have three I don't get how to specify that.

Any help would be greatly appreciated!

==
Versions used:
DESeq2_1.10.0
R version 3.2.2 (2015-08-14) -- "Fire Safety".

You should combine location and treatment into a single factor (see example in the vignette), and use a design of ~ replicate + group.

For the all vs all comparison, you can use a numeric contrast which averages the effects from one location against the other. You can specify this with a numeric vector (corresponding to the order given by resultsNames) or using the list style of contrast with listValues set to 1/4 and -1/4 (because you are averaging four effects for each location).