[BioC] Analysis of Illlumina methylation array data using beadarray

[Ed Schwalbe]

Hello everyone,


My lab is shortly going to run a large cohort of samples (2 X 96 well
plates) on a Goldengate Methylation Array. I have been playing with
the data produced from a pilot study on BeadStudio 3.0 but am finding
that the software has some limitations, specifically relating to QC.

>From my reading, it seems that beadarray would be a good choice for
carrying out more in-depth QC. I have used R before so am capable of
creating a simple script to crunch through QC on all the samples, so I
have a few questions for the experts:

Do I have to spoof beadarray to think that it is importing expression
data? If so, what are the transformations I need to do?
The actual experiment is going to be run at our collaborator's site.
Am I right that for us to receive raw data from BeadScan suitable for
beadarray analysis, the settings.xml file must be altered to output
.txt files.

Finally, does anyone have a feel for an appropriate normalization
technique for this type of data (it returns a beta score which has a
range of 0 to 1, corresponding from fully unmethylated to fully
methylated respectively)? BeadStudio has average (which minimizes
variation across SAMs) and background (removes outliers using a MAD
method) options in a differential methylation analysis.

Thanks for reading, and I'd appreciate any comments you might have.

Ed Schwalbe