[BioC] Analysis of Illlumina methylation array data using beadarray

[Mark Dunning]

Hello Ed,

I think the best option would be work from the raw (bead level) data  
when trying to understand more about the technology. To do this, the  
settings.xml file will indeed need to be modified prior to scanning.  
I can give you more details about that if you're not sure how to do it.

The function readIllumina is designed to work with the bead level  
data from any Illumina assay, so there is no modification needed to  
make it work for methylation.

This will give you a red and green intensity for each bead. After QC  
on the bead level data, you can then choose to summarise the  
replicate red and green values for each bead type  
(createBeadSummaryData) or get an average log-ratio for each bead  
type. I haven't yet implemented a method to get an average beta value  
for each bead type.

The issue of normalisation is a tricky one and I haven't seen a good  
solution yet unfortunately. Unlike gene expression, you can't assume  
most probes will not be differentially expressed or that the  
distribution of signal on each array will be the same. That seems to  
rule out some popular approaches. From the data I have seen, there is  
an obvious dye-bias in the two channels, which could seriously affect  
if you call things as being methylated or not. I think the best you  
can do at this stage is to normalise for this, possibly using  
information from the negative controls. I'd also be interested to  
hear if anyone has any good suggestions though!

Hope this helps,

Mark


On 20 Nov 2007, at 16:00, Ed Schwalbe wrote:

> 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
>
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