Hi Zhiqun,

do you have evidence of nonlinear dye bias effects?  remember, the probes on
the HM27k arrays are paired within the same channel, and all recommended
summary statistics for the assay are based on ratios.  For any pair of
numbers (M, U), both the beta value and the M-value will be identical before
and after rescaling the intensities.  (So for example, a ratio of 1.07 for
Cy3/Cy5 is typical... 1.07*M / (1.07*M + 1.07*U) gives you the same beta,
and log2(1.07*M / 1.07*U ) gives you the same logratio, as not bothering
with any rescaling at all.)  I haven't seen evidence that methods such as
quantile normalization are particularly effective at removing any residual
nonlinearities.

Sensible background correction is important for position-specific effect
amelioration on these chips.  I wrote some patches for methyLumi that can
take advantage of the various control probes to handle dye bias and
background correction; as far as I am concerned, if the lab will not provide
you with (at least) the summarized probe-level intensities, including the
control probes, then you should ask for your money back.  The assay
generates a lot of information via the control probes.  But...

What I'd worry a lot more about if I were you is the plate-specific
hybridization effects.  Regardless of whether you use log-ratios or
beta-values for analysis, if you have replicates and/or randomization,
fitting a variance components model will quickly show where the worst
effects are.

All of the above will get merged into the 'lumi' package going forward,
which I assume will soon have a controlData slot for methylation data
similar to the one for expression data.  'addControlData2lumiMethy' would be
a good idea, maybe I need to write this as a patch?  (Pan?)
You might find it easier to work initially with methyLumi, and then
transition to lumi in the near future.

If you want a quick fix, you can use something like Teschendorff's iSVA to
try and correct some of the effects; I expect to see a decent paper on
normalization in the very near future, as well :-) since most of the
assumptions for expression arrays are false for methylation arrays, and the
most sensible ideas I have seen are all coming from a genotyping perspective
(crlmm, CHARM, etc.)



On Wed, Sep 29, 2010 at 8:40 PM, zhiqun tang <sisitzq@gmail.com> wrote:

> Dear AlI,
> I am very appreciate for your kidly help.
> I am working on the Illumina methylation27 data, I would like to combine
> two
> data from two plates. According to the Illumina's recommendation,
> "Background
> intensity computed from a set of negative controls was subtracted from each
> analytical data point. The ratio of fluorescent signals was then computed
> from the two alleles ā = (max(M, 0))/(|U| + |M| + 100)."
> But a portion of my samples don't have the
> negative_control_Grn_Arg_intensity, some of them even don't have the
> negative_control_red_Arg_intensity.  In that case, how can I estimate the
> background intensity?
> I also know that there is a dye shifting which might effect the combination
> of two dataset. How do I evaluate this dye problem on one plate? How to
> correct them? Which software or tools should I consider? Thank you.
>
> Grace
>
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