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deseq2 design with two variables

Hello, I `ve conducted DEG analysis by Deseq2 and I just want to make sure that I´m right. I have to following information for the design: info:

region: region1, region 1, region 2,
species: species1, species 2, species1
group: region1_species1, region1_species2, region2_species1
(unfortunately, region2_species 2 is missing!)

--> So I have both species from one region, but only species1 in region2 and I want to test for species and region.

Is it ok to use the combined factor (group) to test for my comparisons of interest:

--> differences in species: region1_species1 vs region1_species 2
--> differences in region: region1_species1 vs region2_species1

dds_all<- DESeqDataSetFromMatrix(countData = matrix,
                                 colData = info, 
                                 design = ~ group)

Or is it better to use a nested design (somethink like: ~species+region)?

What I can see so far is a huge effect of species, so it makes sense to separate them (e.g. to test for region within respective species.

deseq2 design

You have only 3 samples?

No within the 3 variables I have 5 replicates

What do you mean with full rank message?

1 answer

It would probably be better to use ~species + region, but you might get the not Full Rank message, in which case, you might have to use your group info instead.

I concur. In this case, there should be no problem with model matrix not having the full rank.

you mean if I use ~group?

I mean if you are using ~species + region.

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