Question: Correlating methylation and expression do i need normalization?
0
gravatar for Pin.Bioinf
2.2 years ago by
Pin.Bioinf270
Malaga
Pin.Bioinf270 wrote:

Hello,

I need to correlate expression values with methylation values. Do I need to normalize expression values from my matrix? What R package do you recommend? Do I need to normalize the beta values for the CpGs?

Thank you in advance

ADD COMMENTlink modified 10 weeks ago by Biostar ♦♦ 20 • written 2.2 years ago by Pin.Bioinf270

Thank you very much,

I realized I have rpkms so it is normalized. I applied smoothing to the methylation values, and I am wondering if i do need to normalize that anyways?

I will take a look at the parallel implementation, it will help me a lot.

Thank you again

ADD REPLYlink written 2.2 years ago by Pin.Bioinf270
1

De nada amigo. Nos vemos / Hasta luego.

PD - if you have beta values, then these are technically already normalised.

PD - if you do want to have the 2 datasets on the same distribution, then I suggest to convert them to the Z-scale with the scale() function in R

ADD REPLYlink modified 2.2 years ago • written 2.2 years ago by Kevin Blighe60k
2
gravatar for Kevin Blighe
2.2 years ago by
Kevin Blighe60k
Kevin Blighe60k wrote:

Your starting point for what you want to perform is indeed a normalised dataset, for both the expression and methylation data. They do not necessarily have to be on the same scale but they should both be normalised. In addition, use Spearman correlation, not Pearson.

Then, provided that your samples are matched between both datasets, you should be able to correlate them easily. Be wary of the fact that, if you attempt to correlate something like 20,000 genes to 34,000 methylation probes, then you will crash R. In this light, take a look at bigcor: https://www.r-bloggers.com/bigcor-large-correlation-matrices-in-r/

Kevin

ADD COMMENTlink modified 16 months ago • written 2.2 years ago by Kevin Blighe60k
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