DEGreport for multifactorial designs
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kavator ▴ 20
@kavator-22955
Last seen 3 months ago

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?

DEGreport • 191 views
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@lorena-pantano-6001
Last seen 13 months ago
Boston

Hi,

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.

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Hi Lorena, thanks for your suggestions! If i were to use res as a pairwise comparison e.g. MutantTreatedNeonatal vs WTTreatedNeonatal, do we define xs="group"? like this?

res2=results(dds,list=c("genotype_Mut_vs_WT", "Mut.Treated.Neonatal")
degplot(dds = dds, genes=vector_with_gene_names, xs ="group",res=res2)


I noticed that all the samplegroups stil appear in the degplot for above^ it perplexes me why so when res2 is only defined for a pairwise comparison.

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if you use genes you don't have to use res. Actually it may confuse what you see. xs should be equal to the column of your colData to use. Probably, genotype if that is the one you are using for the function results.

degPlot will show all the groups, because it is taking all the samples always. If you want only some samples, then subset dds to those samples.