Dear List, I am going to analyze a set of Rattus Norvegicus Nimblegen promoter arrays. briefly, i have 6 slides. in each slide, the ChIP (of a Histon) and the input chromatin have been hybridized. of these 6 slides, 3 are from control animals, and 3 from animals treated with a specific drug. i am interested in finding promoters differently enriched in treated vs control animals. i have not very clear ideas about the steps/BioC-tools of this kind of analysis, so any help is very welcome. thank you very much, yours d -- Dario Greco MSc, PhD student Institute of Biotechnology - University of Helsinki Building Cultivator II, room 223b P.O.Box 56 Viikinkaari 4 FIN-00014 Finland Office: +358 9 191 58951 Fax: +358 9 191 58952 Mobile: +358 44 023 5780 email: dario.greco at helsinki.fi

Hi Dario, Take a look at ACME and/or Ringo. Best, Jim Dario Greco wrote: > Dear List, > > I am going to analyze a set of Rattus Norvegicus Nimblegen promoter arrays. > briefly, i have 6 slides. in each slide, the ChIP (of a Histon) and the > input chromatin have been hybridized. > of these 6 slides, 3 are from control animals, and 3 from animals > treated with a specific drug. > > i am interested in finding promoters differently enriched in treated vs > control animals. > > i have not very clear ideas about the steps/BioC-tools of this kind of > analysis, so any help is very welcome. > > thank you very much, > yours > d > -- James W. MacDonald, M.S. Biostatistician Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623

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Hi Dario, depending on the type of arrays you have, the Bioconductor packages Ringo and oligo may be of interest to you. Please have a look at their vignettes. I guess you mean that in your ChIP an antibody against a histone tail modification has been used. We have created and used the package Ringo, which relies on limma, for such an analysis, but there are also a number of other valuable approaches available through Bioconductor, for example ACME Hope this helps to get you started, Joern Dario Greco wrote: > Dear List, > > I am going to analyze a set of Rattus Norvegicus Nimblegen promoter arrays. > briefly, i have 6 slides. in each slide, the ChIP (of a Histon) and the > input chromatin have been hybridized. > of these 6 slides, 3 are from control animals, and 3 from animals > treated with a specific drug. > > i am interested in finding promoters differently enriched in treated vs > control animals. > > i have not very clear ideas about the steps/BioC-tools of this kind of > analysis, so any help is very welcome. > > thank you very much, > yours > d >

I suggest that - after array normalization (i recommend vsn) - you apply common statistics used for differential gene expression (e.g. moderated t-statistics) on a probe level (control vs. treatment). for the t-statistics you should only look at probes that are - within the arrays of an experimental group - significantly enriched for your histone modification before or after treatment. you then can e.g. set a threshold (fdr-based) and define significantly changed probes. afterwards you combine adjacent significantly changed probes using either a sliding window or a hidden markov model as on tiling arrays you have to assume that more than single probes will respond due to the chromatin resolution that spans more than one probe. that will reveal changed regions that - hopefully - locate where you hope ;-) on promoters. sounds complicated but shold be fairly easy.. if you are a bit familiar with R! best T On Jan 17, 2008, at 4:59 PM, Dario Greco wrote: > Dear List, > > I am going to analyze a set of Rattus Norvegicus Nimblegen promoter > arrays. > briefly, i have 6 slides. in each slide, the ChIP (of a Histon) and > the > input chromatin have been hybridized. > of these 6 slides, 3 are from control animals, and 3 from animals > treated with a specific drug. > > i am interested in finding promoters differently enriched in treated > vs > control animals. > > i have not very clear ideas about the steps/BioC-tools of this kind of > analysis, so any help is very welcome. > > thank you very much, > yours > d > > -- > Dario Greco > MSc, PhD student > Institute of Biotechnology - University of Helsinki > Building Cultivator II, room 223b > P.O.Box 56 Viikinkaari 4 > FIN-00014 Finland > Office: +358 9 191 58951 > Fax: +358 9 191 58952 > Mobile: +358 44 023 5780 > email: dario.greco at helsinki.fi > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor ====================================================================== Dr. Tobias Straub Adolf-Butenandt-Institute, Molecular Biology tel: +49-89-2180 75 439 Schillerstr. 44, 80336 Munich, Germany

Dear Jim and Joern, thank you very much for your quick reply. I was just giving a look to the ACME and Ringo packages. as far as I understand, it is quite "simple" to look for enrichment of the antibody over the input signals (Cy5/Cy3 in my case). but what would be the best way to look for significant differences between the two groups (treated vs control animals)? thank you once more, d -- Dario Greco MSc, PhD student Institute of Biotechnology - University of Helsinki Building Cultivator II, room 223b P.O.Box 56 Viikinkaari 4 FIN-00014 Finland Office: +358 9 191 58951 Fax: +358 9 191 58952 Mobile: +358 44 023 5780 email: dario.greco at helsinki.fi Calvin: "As far as I'm concerned, if something is so complicated that you can't explain it in 10 seconds, then it's probably not worth knowing anyway". Bill Watterson, The Indispensable Calvin and Hobbes