[BioC] Analyzing "differential variability" of methylation (and gene expression)

[Brent Pedersen]

This was for charm data:
http://biostatistics.oxfordjournals.org/content/13/1/166
but could be a starting point after adjusting for cell-types? As
implemented (http://biostat.jhsph.edu/~ajaffe/code/vmrFinder.R) , it
only allows for dichotomous covariate.

On Fri, May 10, 2013 at 8:59 AM, Simone <enomis.bioc at gmail.com> wrote:
>> Read Houseman's paper and use the sorted cells from Juha Kere's lab to calibrate.
>
> Thank you very much for the recommendations. I read both papers and as
> far as I can see I could use the method of Houseman et al. with the
> signature provided (which they say is not not affected by age) to
> estimate proportions of celltypes for every sample I have got, and
> then add these values as covariates to my model, to see if cell type
> distribution changes have an effect.
>
> And furthermore, for my 450K dataset I think I could apply Houseman's
> method on the purified cell data of Reinius/Kere to obtain such a
> signature for the 450K platform as well, and do the same again.
>
> Right?
>
> What I found interesting is that Reinius et al. write in their paper:
> "Methylation in the promoter CpG islands tends to be low and very
> similar among all the cell types and for those CpG sites, measurements
> in whole blood would reflect the methylation status across cell
> populations". Wouldn't this mean that for data obtained by the 27K
> microarray, which has its probes located in CpG islands of gene
> promoters, there would not be such a "subpopulation change effect"
> counfounding methylation measures of whole blood?
>
> However, I will try to see what happens in my data (both 27K and 450K).
> Reinius also says, that "the differential cell count in whole blood
> was similar for all six donors", maybe because they did not cover such
> wide age ranges (24 yrs - 52 yrs while I have got data from newborns
> to ~ 100 yrs old).
>
> Although data is only for seven or eight main leukocytic cell types
> available, I think it will be very good (and important) to see what
> happens when adjusting (at least) for those subtypes. I always find it
> odd when new papers coming out in the context of methylation and aging
> say that their observations are not due to blood composition changes
> although they look at whole blood samples referring to the paper of
> Rakyan et al. from 2010 where they sorted CD14+ monocytes and CD4+ T
> cells and concluded that there is a significant correlation between
> the two when looking at hypermethylated regions but _not_ for
> hypomethylation, when the change predominantly ocurring in blood with
> age is _hypo_methylation! The conclusion of Rakyan's paper actually
> was that hypomethylated regions "probably reflect aging-associated
> changes in the relativ proportion of cell subtypes in whole blood",
> and not the contrary ...
>
> Now that I am aware of Houseman's method and the data, I can at least
> try to do a little better. Thanks a lot for your help!
>
> Simone
>
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