Hi,

I'm currently exploring the functions in DESeq2 and try to replicate some findings of DOI: 10.1126/science.aan3456. In this paper, they test several models to identify clusters of differentially expressed genes between 3 species (H[uman]/C[himp]/M[acaque]). Some of their models they test are as followed: Model 0: count ~ Batch Model H: count ~ species + batch (2 levels of species: human, chimpanzee/macaque) Model A: count ~ species + batch (3 levels of species: human, chimpanzee, macaque)

To identify clusters of genes where H > C > M, they first test Model H vs reduced model 0. This also works fine in my code, as I can easily drop the complete factor species. However, I can't figure out how to combine chimpanzee/macaque, ultimately having something like:

dds <- DESeqDataSetFromMatrix(countData=counts, colData=metaData, design=~Batch + ModelA)
dds <- DESeq(dds, test="LRT", reduced = ~Batch + ModelH)

As this gives the error:

Error in checkLRT(full, reduced) : 
  the following variables in the reduced formula not in the full formula: ModelH

Does anyone have an idea how to reduce the factor specie from 3 to 2 for the reduced model, so I can compare these 2 models?

Thanks in advance!

This approach should work:

> species1 <- factor(rep(1:2,c(5,10)))
> species1
 [1] 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2
Levels: 1 2
> species2 <- factor(rep(1:2,c(10,5)))
> species2
 [1] 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2

Then just using ~species1 + species2 gives the following design matrix:

> model.matrix(~ species1 + species2)
   (Intercept) species12 species22
1            1         0         0
2            1         0         0
3            1         0         0
4            1         0         0
5            1         0         0
6            1         1         0
7            1         1         0
8            1         1         0
9            1         1         0
10           1         1         0
11           1         1         1
12           1         1         1
13           1         1         1
14           1         1         1
15           1         1         1