Question: Filtering & validation strategies for methylation analysis without normal controls
gravatar for mathias.heydt
12 months ago by
mathias.heydt90 wrote:

Hi all

I am currently analyzing 450K methylation data, trying to find differentially methylated probes without normal controls - until I do have normal data.

InfiniumPurify (Zheng et al. 2017) can calculate differentially methylated cpgs when no normal controls are available. The problem is that you don't have any delta beta (difference in methylation) values for the resulting DMCs. So I can't filter on minimum difference in methylation value, or set a baseline threshold for reproducibility in later validation.

Can anyone recommend anything I might try to explore until I have normal data? I just recently started working with methylation data and epigenomics in general.

Additionally; before using InfiniumPurify I was using ChAMP, comparing my data against normal data from other tissues (I know...). InfiniumPurify basically refined this procedure, and I switched methods. I looked at common results in the sorted top 50K probes from both techniques. They don't share a lot of common results, but there is a small peak of common highly-significant probes. I'm a PhD student, and I have almost no experience, but is this something I could further investigate? I've got really nothing else to filter on, except for this shared result.

intersection of results of two methods, absolute percentage (50K) and relative to the amount of results that are sequentially evaluated

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