Hi Folks I really like the package DEGreport and I hope to be able to utilize it However, I have a 3x2 matrix (each factor has 2 levels) with the following dds dds<-genotype,treatment, age, genotype:traetment, genotype:age, genotype:age:treatment. I factor in all of them to ~group with

 dds$group <- factor(paste0(dds$genotype, dds$condition,dds$agegroup))

i wanted to use the function degPlot and the following is my command as

res=results(dds)
    degplot(dds = dds, res = res, n = 6, xs ="group")

Can i cross check if this is correct if i want to evaluate the top 6 genes across all my groups? It's not clear to me how i can select specific pairwisegroups like MutantTreatedNeonatal vs WTTreatedNeonatal

also does degsignature only compare 2 factors? as shown here- http://lpantano.github.io/DEGreport/articles/DEGreport.html#general-qc-figures-from-de-analysis is it possible that i can compare 3 variables based on my experimental design?

Hi,

Thanks for your question.

That would give you the top 6 genes from the res object from results, so whatever you did to get res, that is the comparison you are looking at this.

If you want all the comparisons, you can get the top significant genes from each comparison and use the function as:

res=results(dds)
    degplot(dds = dds, genes=vector_with_gene_names, xs ="group")

There are some functions in the package to get top significans: http://lpantano.github.io/DEGreport/reference/significants.html. If you create a list of res (one for each comparison) with http://lpantano.github.io/DEGreport/reference/DEGSet.html, then you can use significants function only once, and it will give you genes significants across conditions.