Hi,

I am analyzing methylation data, I have two files with beta values one for disease samples and another for control samples.

I would like to convert both disease and control beta values in to M values and calculate Fold change of disease/control using M values

I checked many articles and found that in some studies only beta values were used and delta B was calculated to assess DMR.

I tried both ways in the following example and found that different ways could give different assessemnt for a probe or position but i got different results

disease=.73

cont=.57

M_disease=1.434937

M_control=0.4066253

FC=M_disease/M_control=3.528893 which is differentially methylated in case threshold is 2 fold

delta B=.73-.57=.0.16 #NOT differentially methylated in case threshold=.2

Any one has an experience which has more robust output, using either delta B or FC for instance or using p-value of statistical tests as implemented in many R packages.

Any help is appreciated

Thanx Peter. The data I have came from illumina K27 methylation arrays which minfi package does not support. Are there other packages that support illumina K27 arrays?

You might try the lumi package. The vignette discusses analysing Illumina 27k data

Hi Peter,

I checked a bit older user guide which mentioned that illumina 27k is not supported.

Thank you very much for the link to latest vignette

To clarify, "minfi" does not currently support Illumina 27k but "lumi" does (these are different packages).