Yes, we use Nimblegen two-color. thx -----Original Message----- From: seandavi@gmail.com [mailto:seandavi@gmail.com] On Behalf Of Sean Davis Sent: Friday, July 18, 2008 2:09 PM To: Christian Feller Cc: Wolfgang Huber; bourgon at ebi.ac.uk; bioconductor at stat.math.ethz.ch Subject: Re: [BioC] GC-content sensitive normalization of Affymetrix tiling arrays for ChIP-chip On Fri, Jul 18, 2008 at 5:32 AM, Christian Feller <feller.christian at="" gmail.com=""> wrote: > Dear Wolfgang, > > thank you for your reply! > My goal is to compare my own ChIP-chip data (Nimblegen tiling) with some > other ChIP-chip data (created on Affymetrix tiling). I normalized my data > with vsn and got some nice signal-to-noise ratios (visual inspection, > replicates show same trend). When I normalize with other algorithms (loess, > quantile, Tukey-biweight) I get a similar output (based on visual inspection > and correlation among them). > > Now, I normalized the Affymetrix data with vsn and got some terrible > signal-to-noise ratios. One possible explanation might be the shorter probe > sequence of the Affy probes compared to the Nimblegen probes. Fluorescence > signals of shorter probes are more sensitive to the underlying sequence (in > particular GC-content). Because vsn does not account for the GC- content I > reasoned to try to adjust for it (therefore, I thought about using GCRMA). I assume that the Nimblegen data are two-color? If so, that accounts for the vast majority of the differences you observe, I would imagine. If not, then for single-color nimblegen arrays, I would expect that GC correction would be useful, also. However, such a correction probably does not need to account for the base positions, but only the GC count. Sean > I will try to use the normalizeByReference function and report back when it > works. > > Thanks again! > > Best wishes, > Christian > > -----Original Message----- > From: Wolfgang Huber [mailto:huber at ebi.ac.uk] > Sent: Friday, July 11, 2008 12:55 AM > To: Christian Feller > Cc: 'Sean Davis'; bourgon at ebi.ac.uk; bioconductor at stat.math.ethz.ch > Subject: Re: [BioC] GC-content sensitive normalization of Affymetrix tiling > arrays for ChIP-chip > > Dear Christian, > > few points: > > - 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 > somewhere else. > > - 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 [1], but I > have only used it on RNA expression data, not on ChIP, so porting it to > that application would need some care. > > [1] http://bioinformatics.oxfordjournals.org/cgi/reprint/22/16/1963.pdf > > Best wishes > Wolfgang > > > > > > > > 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! >> >> Best >> Christian >> >> -----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. >> >> Sean > >