[BioC] Illumina Methylation. Normalization and statistics

[Michael Walter]

Dear Sean,

Thanks for your answers. I have one array probed with fully methylated DNA purchased by ZYMO. Here all beta values should be 1, which they aren't, of course. Can I use these values to normalize the rest of my arrays? Let assume my fully methylated value is 0.7 and my actual value is 0.5 then I would correct my beta to 0.5/0.7?

best Regards,

Mike





> -----Ursprüngliche Nachricht-----
> Von: "Sean Davis" <sdavis2 at mail.nih.gov>
> Gesendet: 19.11.08 16:30:15
> An: "Michael Walter" <michael.walter at med.uni-tuebingen.de>
> CC: bioconductor at stat.math.ethz.ch
> Betreff: Re: [BioC] Illumina Methylation. Normalization and statistics


> On Wed, Nov 19, 2008 at 10:18 AM, Michael Walter <
> michael.walter at med.uni-tuebingen.de> wrote:
> 
> > Dear List,
> >
> > We run our first slide of illumina's infinium methylation arrays. After
> > searching the archive, I still have some general questions how to best
> > analyze the data.
> >
> > First of all, I'm would like to know some opinion on normalization. In my
> > personal and probably simplistic view I'd think that normalization is not
> > necessary since the value you get from the array is a ratio which is sample
> > inherent (unlike a classical two-color expression array where you mix two
> > samples to generate the expression ratio). Is this assumption correct or am
> > I missing some important aspect?
> >
> 
> Unfortunately, there is a significant dye-bias issue.  That is, there is a
> propensity for one dye to be brighter than the other and it appears that
> Illumina does not adequately correct for this bias.
> 
> 
> >
> > Anyway, I'd like to perform background normalization which results as usual
> > with illumina arrays in some negative values. Does anyone one have a neat
> > solution for this problem or shall I just skip the probes?
> >
> 
> I have been just ignoring those probes.
> 
> 
> >
> > Do I have to correct for some dye effect like for the golden gate
> > methylation assay? Since the probes for methylated and unmethylated DNA
> > incorporate the same dye this shouldn't be an issue?
> >
> 
> See above.
> 
> 
> >
> > My final question is basically the most pressing: What kind of statistic
> > test should I use? Since all the values are ratios between 0 and 1 I have a
> > real bad feeling by simply running some t-tests. And if a t-test is the
> > proper choice, shall I log-transform the data?
> >
> 
> The t-statistic should still be valid, I think.  The assumptions that go
> into statistics like the t-stat are not based on the distribution of the
> data, but on differences between values.  I think these assumption probably
> still holds in practice for these data.  However, I have not tried to prove
> things one way or the other.  Of course, if you are concerned about,
> non-parametric testing will alleviate these concerns.
> 
> Sean
> 
> 
> >
> > Any input and shared experience with this type of array is highly
> > appreciated.
> >
> >
> > Best Regards,
> >
> >
> > Mike
> > --
> > Dr. Michael Walter
> >
> > The Microarray Facility
> > University of Tuebingen
> > Calwerstr. 7
> > 72076  TÃŒbingen/GERMANY
> >
> > Tel.: +49 (0) 7071 29 83210
> > Fax. + 49 (0) 7071 29 5228
> >
> > Confidentiality Note:\ This message is intended only for...{{dropped:9}}
> >
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> >
> 
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> 
> 
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-- 
Dr. Michael Walter

The Microarray Facility
University of Tuebingen
Calwerstr. 7
72076  Tübingen/GERMANY

Tel.: +49 (0) 7071 29 83210
Fax. + 49 (0) 7071 29 5228

Confidentiality Note:\ This message is intended only for...{{dropped:9}}