I have 3 muscles I am trying to perform differential expression with.
For each muscle type, I have 3 replicates.
How can I get pairwise comparisons between muscle 1 vs muscle 2, muscle 1 vs muscle 3, muscle 2 vs muscle 3. Within the DESeq2 tool I have factor set to muscle, then level 1 as muscle 1, level 2 and muscle 2, etc. Then within each level/,muscle type, I select the three replicate data count files.
I read that DESeq2 takes the first input as the reference (so that would be muscle 1) and then compares everything to that. But thatās not necessarily what I want. I have been using Cuffdiff to perform analyses but wanted to use a more updated tool but I canāt seem to set it up as it needs to be. Can anyone give me some guidance?
Iām aware of the math to an extent, but ultimately, when youāre building a model of expression change in a gene and comparing it to a normal distribution, the model incorporates each sampleās expression level, so idk how to get pairwise comparisons of LFCs/significance from a matrix with multiple factors/variables and the levels therein.
I have a bunch of RNAseq data from mutant mice at different ages; and the data clusters better after including age as an additional factor (genotype is my primary factor), and the test results are different if I remember right, but ultimately, how do you do a pairwise test (contrast) or examine interactions on Galaxy? The DESeq2 paper is very intuitive until you dig deeper into the methods. The documentation in Bioconductor for the DESeq2 R package is good, but is there the appropriate functionality here on Galaxy for this?
It almost seems that itās not available as part of the Galaxy wrapper. Ultimately, I ended up ditching DESeq2 and ended up using edgeR as I found that their set up made more sense to me. I also found it easier to manipulate.
Yes, EdgeR and Limma offer more functions and the tool forms are structured a bit differently.
Search with the keywork āedgerā here to review prior Q&A and tutorial links, including tutorials that are still in progress for final publication to the Galaxy Training Network (GTN): Galaxy Training!
I am in a similar position regarding my RNA-seq analysis. I followed the āreads to countsā tutorial and performed DSeq2.
The parameters I used for DeSeq2 is below.
Factor 1: Treatment
Factor level1: CONTROL
Factor level 2: Drug 1
Factor level 3 : Drug 3
I wanted to make the following comparisons (and the corresponding plots).
Control vs Treatment 1
Control vs Treatment 2
Treatment 1 vs Treatment 2
Control vs Treatment 1 + Treatment 2 combined
Below is a screen shot of my DeSeq2 results tables. I have three factor levels (in the order mentioned above), but I donāt understand the log2(FC) shown in the table is a comparison between which factor levels (1 and 2 or 2 and 3 or 1 and 3 ?) Or should I use some other tool? Please suggest.
