[BioC] GC-content sensitive normalization of Affymetrix tiling arrays for ChIP-chip
huber at ebi.ac.uk
Fri Jul 11 00:54:32 CEST 2008
- afaIu the background correction method of GC-RMA does not make use of
probe sets, it works on individual probes. Probe sets only come into
play later, for the expression estimate. But getting it to work for your
use case may be a hard problem (has anyone on the list managed?)
- vsn2 does not do probe-sequence specific adjustments, so I am not
sure why it was mentioned in this context.
- the choice of language should be secondary to these criteria: quality
of the underlying science and of the implementation.
- you say "how can I take into accound (sic) the GC-effect of single
probes", but would it make sense to take a step back and tell us why you
want to do that and what you want to achieve? Perhaps your answer is
- the normalizeByReference function in the tilingArray package offers a
method to do probe(sequence)-specific background correction for
Affymetrix tiling array data, and is described in a paper , but I
have only used it on RNA expression data, not on ChIP, so porting it to
that application would need some care.
Christian Feller wrote:
> Hi Sean,
> Thank you for your quick response! We successfully used MAT under Python for a dataset with 3 control arrays (hybridized with input) and 3 IP arrays (all biological replicates). In comparison with vsn2, probe standardization via MAT significantly increased the signal-to-noise ratio. However, we have still some doubts about the reliability of those results since the raw data seem to be very noisy, and the correlation of the biological replicates is not very strong.
> Thanks again!
> -----Original Message-----
> From: seandavi at gmail.com [mailto:seandavi at gmail.com] On Behalf Of Sean Davis
> Sent: Wednesday, July 09, 2008 2:04 AM
> To: Christian Feller
> Cc: bioconductor at stat.math.ethz.ch; bourgon at ebi.ac.uk
> Subject: Re: [BioC] GC-content sensitive normalization of Affymetrix tiling arrays for ChIP-chip
> On Tue, Jul 8, 2008 at 6:58 PM, Christian Feller
> <feller.christian at gmail.com> wrote:
>> Dear Richard Bourgon and list,
>> I am a newbie in analyzing ChIP-chip Affymetrix tiling arrays (GeneChip
>> Drosophila Tiling 1.0R Array).
>> My question is how can I take into accound the GC-effect of single probes if
>> I do not have expression sets (due to the nature of a tiling array)? We had
>> the idea of taking a fixed window size, defining the probes within them as a
>> "probeset", and using GCRMA for background correction/normalization. In
>> addition, can we use this configuration (normalization via GCRMA) for
>> profiles with broad ChIP-enriched regions (as it is the case for many
>> histone modifications).
>> If there are some additional advice especially for the pre-processing steps
>> I would be very happy!
>> Until now, we do the normalization using vsn2.
> Hi, Christian. Do you have the input DNA from which you are going to
> form a ratio, or are you attempting to do a single-channel analysis?
> If the latter, then you might look at MAT from Shirley Liu's group. I
> don't think it is available for R, but the algorithm could probably be
> coded in R relatively easily. There are likely other solutions.
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