Question: RNA-Seq Differential gene expression
0
gravatar for umeshtanwar2
10 months ago by
umeshtanwar210
umeshtanwar210 wrote:

Hi, I have the samples for 4 plant types (WT, KO1, KO2 and OE1) in three replicates, Mock treated and after stress treatment. So in total 24 samples (4 Mock and 4 Treated, 3 replicates of each). I would like to analyse the differential gene expression in each sample type before treatment (Mock) and after treatment. I used STAR for alignment of reads on reference genome. Then I obtained count.txt files for each sample by using the tool featureCounts. Now I would like to analyse the differential gene expression using edgeR. But I am having problem in creating the matrix as I have a large number of samples. Could you please help me in that?

Thanks

rna-seq • 286 views
ADD COMMENTlink written 10 months ago by umeshtanwar210

What have you tried in terms of your model matrix? What are the comparisons you would like to make?

ADD REPLYlink written 10 months ago by Devon Ryan93k

Thank you Devon Ryan. I would like to make comparisons within the plant types (WT vs KO1, Wt vs KO2, WT vs OE1, Mock and treated samples).

ADD REPLYlink written 10 months ago by umeshtanwar210
1

So a design of ~group+treatment would work.

ADD REPLYlink written 10 months ago by Devon Ryan93k

Following this link you'll find a paper explaining how to use EdgeR and how to properly set a contrast matrix that will help you making the correct comparisons:

https://f1000research.com/articles/5-1408/v3

If you don't do KO1 vs KO2 or KO2 vs OE1 comparisons, perhaps it is better to only consider running the DEG analysis on WT vs KO1, then WT vs KO2, etc.

Having everything in one go is better as you can compare everything to everything. The downside is that it is hard to find a consensus when removing the lowly / unexpressed genes, and because of this you might discard important genes. But if you are not stringent enough, you'll end up with an incorrect normalisation and scaling factors.

ADD REPLYlink modified 10 months ago • written 10 months ago by Gautier Richard280
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