Question: Assessing DMRs between treatment groups: subtracting control group DMRs to account for "baseline" methylation
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gravatar for Ellen O
18 months ago by
Ellen O10
Stellenbosch University
Ellen O10 wrote:

I am currently awaiting Illumina methylationEPIC (850k) data and in the mean time figuring out how to assess DMRs with demo data. I am new to these analyses but I am making use of the Maksimovic et al. cross-package workflow (https://f1000research.com/articles/5-1281/v2), which I have found very useful thus far.

I have three sample groups: healthy controls, poor treatment responders, and good treatment responders. I was wondering if it is possible to "subtract" the differential methylation seen within the controls before comparing the two treatment groups, so that I can account for a baseline/ "normal" level of variable methylation. Would this be possible in limma, minfi or any other packages? Or would it make more sense to just compare all three groups to each other?

Thanks in advance for any assistance!

ADD COMMENTlink modified 14 months ago by hongbo91920 • written 18 months ago by Ellen O10
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gravatar for andrew.j.skelton73
18 months ago by
London
andrew.j.skelton735.3k wrote:

Others may be able to correct me if I'm wrong... but if you're making a contrast matrix in Limma, you could just do something along the lines of:

(healthy_control - poor_response) - (healthy_control - good_response)
ADD COMMENTlink written 18 months ago by andrew.j.skelton735.3k

Thanks Andrew, I will try it out!

ADD REPLYlink written 18 months ago by Ellen O10
0
gravatar for hongbo919
14 months ago by
hongbo91920
hongbo91920 wrote:

I suggest using the DMR identification software based on entropy such QDMR (for pre-defined regions) or SMART (for de novo identification of DMRs from BS-Seq data). As there are multiple samples in the same group, the DMC function of SMART should work for your project.

ADD COMMENTlink written 14 months ago by hongbo91920
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