[BioC] Limma for DNA methylation arrays?

Gordon K Smyth smyth at wehi.EDU.AU
Sat Nov 30 00:41:15 CET 2013

Hi Tim,

I have never analysed data from any of the newer DNA methylation array 
technologies, so you should ask someone who has how well the limma 
pipeline seems to work on that type of data.

For example, Alicia Oshlack's group develops methods for methylation 
arrays and finds limma useful:


It seems very reasonable to me to suppose that methylation data has 
special variance structures that could be advantageously taken into 
account.  I doubt though that this means abandoning the empirical Bayes 
approach entirely, as it is not very dependent on normality or 
independence and gives some benefit in a wide range of situations.  You 
will notice that I recommended to the original poster that they used 
eBayes() with trend=TRUE.

Best wishes

On Fri, 29 Nov 2013, Tim Triche, Jr. wrote:

> Is eBayes generally regarded as appropriate for DNA methylation microarray
> probes, i.e. is the general consensus that departure from normality and
> shared variance structure is "normal enough" to shrink towards a global
> prior distribution whose parameters have been estimated from a potentially
> mixed population?  e.g. concerns could involve the probe type (paired vs.
> unpaired), variance structure (which with m-values, one assumes these are
> at least approximately normal), and the degree of sharing (e.g. nearer
> probes tend to be more correlated than further probes, and probes in
> certain regions tend to be inherently more variable across datasets than
> probes in other regions).
> I've been meaning to ask for your thoughts on this for quite some time :-)
> Best,
> --t
> *He that would live in peace and at ease, *
> *Must not speak all he knows, nor judge all he sees.*
> Benjamin Franklin, Poor Richard's
> Almanack<http://archive.org/details/poorrichardsalma00franrich>

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