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

Simone enomis.bioc at gmail.com
Fri May 10 16:59:22 CEST 2013


> 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



More information about the Bioconductor mailing list