Hi, I have a CGH data set (two colour spotted array data) where i have performed various filtering and normalisation steps using LIMMA. I now have a matrix of log ratios and was wondering which are people's preferred functions or tools to call genes as present or absent? thanks for any advice Adam

You may want to try the segment function of DNAcopy to identify regions with gains or losses. If you then would like to identify regions whowing gains/losses across samples, look at packages like CNTools, cghMCR, CGHcall, and CGHregions. >X-Original-To: jzhang at jimmy.harvard.edu >Delivered-To: jzhang at jimmy.harvard.edu >X-IronPort-Anti-Spam-Filtered: true >X-IronPort-Anti-Spam-Result: AmoAAJ83WUuBhJEPkWdsb2JhbACBRZpiAQEBAQkLCgcTBbt2hDwE >X-IronPort-AV: E=Sophos;i="4.49,324,1262581200"; d="scan'208";a="146786654" >X-SBRS: 4.5 >X-Spam-Checker-Version: SpamAssassin 3.2.5 (2008-06-10) on hypatia.math.ethz.ch >X-Spam-Level: >X-Spam-Status: No, score=-4.6 required=5.0 tests=AWL, BAYES_00, RCVD_IN_DNSWL_MED autolearn=ham version=3.2.5 >Mime-Version: 1.0 (Apple Message framework v1077) >X-Mailtags-Uuid: 9957FA95-FEA0-4267-B955-E917C15C1F2C >From: adam_pgsql <adam_pgsql at="" witneyweb.org=""> >X-Mailtags-Timestamp: 2010-01-22 13:28:23 +0000 >Date: Fri, 22 Jan 2010 13:28:23 +0000 >X-Mailtags-Version: 2.5 >To: BioConductor List <bioconductor at="" stat.math.ethz.ch=""> >X-SGUL-MailScanner-Information: Please contact the ISP for more information >X-SGUL-MailScanner-ID: 1NYJYm-0005no-8I >X-SGUL-MailScanner-MH1: Found to be clean >X-SGUL-MailScanner-SpamCheck: not spam, SpamAssassin (not cached, score=-4.399, required 5, autolearn=not spam, ALL_TRUSTED -1.80, BAYES_00 -2.60) >X-SGUL-MailScanner-From: adam_pgsql at witneyweb.org >X-USF-Spam-Status: No >X-Tag-Only: YES >X-Filter-Node: phil3.ethz.ch >X-USF-Spam-Level: -- >X-USF-Spam-Status: hits=-2.5 tests=BAYES_00,FORGED_RCVD_HELO >X-USF-Spam-Flag: NO >X-Virus-Scanned: by amavisd-new at stat.math.ethz.ch >Subject: [BioC] Calling genes present or absent in CGH data >X-BeenThere: bioconductor at stat.math.ethz.ch >X-Mailman-Version: 2.1.13 >List-Id: The Bioconductor Project Mailing List <bioconductor.stat.math.ethz.ch> >List-Unsubscribe: <https: stat.ethz.ch="" mailman="" options="" bioconductor="">, <mailto:bioconductor-request at="" stat.math.ethz.ch?subject="unsubscribe"> >List-Archive: <https: stat.ethz.ch="" pipermail="" bioconductor=""> >List-Post: <mailto:bioconductor at="" stat.math.ethz.ch=""> >List-Help: <mailto:bioconductor-request at="" stat.math.ethz.ch?subject="help"> >List-Subscribe: <https: stat.ethz.ch="" mailman="" listinfo="" bioconductor="">, <mailto:bioconductor-request at="" stat.math.ethz.ch?subject="subscribe"> >Content-Transfer-Encoding: 7bit > >Hi, > >I have a CGH data set (two colour spotted array data) where i have performed various filtering and normalisation steps using LIMMA. I now have a matrix of log ratios and was wondering which are people's preferred functions or tools to call genes as present or absent? > >thanks for any advice > >Adam > >_______________________________________________ >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 Jianhua Zhang Department of Medical Oncology Dana-Farber Cancer Institute 44 Binney Street Boston, MA 02115-6084

On Fri, Jan 22, 2010 at 8:28 AM, adam_pgsql <adam_pgsql at="" witneyweb.org=""> wrote: > Hi, > > I have a CGH data set (two colour spotted array data) where i have performed various filtering and normalisation steps using LIMMA. I now have a matrix of log ratios and was wondering which are people's preferred functions or tools to call genes as present or absent? > Hi, Adam. CGH data are generally treated somewhat differently than gene expression and so a different set of tools is often used. You might look at any of a dozen or so methods related to CGH segmentation. There is a literature comparing various methods, also. For starters, you might look here: http://bioconductor.org/packages/release/CopyNumberVariants.html For literature, consider checking out this as a "review": http://www.ncbi.nlm.nih.gov/pubmed/16081473 And for an interesting approach to comparison between methods, see: http://www.ncbi.nlm.nih.gov/pubmed/18296463 Sean