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!