Hello!

First of all, I'm very sorry I could not reply earlier, and thank you very
much for answering my question on how to analyze differences in the
variability of methylation and expression values with aging.


> From: Pekka Kohonen

> I also find this an interesting question. I don't have a solution
> handy but I would say that using linear models seems preferable
> because you can discount in the model other sources of variation. For
> instance batch effects, other confounding variables/covariates
> (smoking?, bmi?) and so on that are not age-related.

Yes, this is also what we were thinking about. But I am not sure about how
to model variability (gene-wise) in such an approach. Whenever I would like
to add any variability measure for a gene in a simple linear model, I would
have to build groups of ages previously (if not, I don't know where
increased or decreased variability with increasing age should come from,
but maybe I am missing something, my experience with building such models
is very limited so far), but this (building of groups) is exactly what was
suggested to avoid.


> From: Tim Triche, Jr.

> From an article on mixture models for simultaneously detecting
differences
> in the mean and variance, by Haim Bar and Jim Booth, which is by far the
> best I've read.

Thank you very much for mentioning this very interesting paper. I don't
know why I haven't found it before, I should have, because it deals
(almost) exactly with the problem I want to solve. And it sounds really
good! The only thing is, that for the method the author describes in his
paper, I would also need to build age groups to be able to then compare the
differences between the two groups. But as I already wrote above, I'm not
sure if it would really be easily possible to work without age groups
anyway.

As I was very interested in the approach of the paper and could not find
the corresponding code neither an R package, I contacted Haim Bar via
e-mail. He told me that he could provide the code and that he's currently
generalizing the model to handle more groups and also covariates (including
continuous variables), which is what I was looking for. So probably this
will be the way to go for me.

However, I think I'll also have to come back to discuss the issue with
those who told me not to use age groups for my analysis, to get things
clearer.

Thank you for your help.

Best,
Simone

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