Dear list, Some months ago, I read the following paper: http://bioinformatics.oxfordjournals.org/cgi/content/abstract/23/13/i2 82 It is said:"we identify a crucial step in GCRMA responsible for introducing severe artifacts in the data leading to a systematic overestimate of pairwise correlation. This has key implications not only for reverse engineering but also for other methods, such as hierarchical clustering, relying on accurate measurements of pairwise expression profile correlation. We propose an alternative implementation to eliminate such side effect". I've checked the papers that reference this work, but no one is about the improvement of GCRMA. Does anyone know if, after this paper was published, GCRMA was fixed? Thanks, Javier

Dear Javier, On Feb 1, 2010, at 10:24 AM, Javier P?rez Florido wrote: > Dear list, > Some months ago, I read the following paper: > http://bioinformatics.oxfordjournals.org/cgi/content/abstract/23/13/ i282 > > It is said:"we identify a crucial step in GCRMA responsible for > introducing severe artifacts in the data leading to a systematic > overestimate of pairwise correlation. This has key implications not > only for reverse engineering but also for other methods, such as > hierarchical clustering, relying on accurate measurements of > pairwise expression profile correlation. We propose an alternative > implementation to eliminate such side effect". > > I've checked the papers that reference this work, but no one is > about the improvement of GCRMA. Does anyone know if, after this > paper was published, GCRMA was fixed? > > Thanks, > Javier > > _______________________________________________ > 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 I believe that it was fixed in most recent versions. Best wishes, Rich ------------------------------------------------------------ Richard A. Friedman, PhD Associate Research Scientist, Biomedical Informatics Shared Resource Herbert Irving Comprehensive Cancer Center (HICCC) Lecturer, Department of Biomedical Informatics (DBMI) Educational Coordinator, Center for Computational Biology and Bioinformatics (C2B2)/ National Center for Multiscale Analysis of Genomic Networks (MAGNet) Room 824 Irving Cancer Research Center Columbia University 1130 St. Nicholas Ave New York, NY 10032 (212)851-4765 (voice) friedman at cancercenter.columbia.edu http://cancercenter.columbia.edu/~friedman/ In Memoriam, Patrick McGoohan

It has been updated. Jean Javier P?rez Florido wrote: > Dear list, > Some months ago, I read the following paper: > http://bioinformatics.oxfordjournals.org/cgi/content/abstract/23/13/ i282 > > It is said:"we identify a crucial step in GCRMA responsible for > introducing severe artifacts in the data leading to a systematic > overestimate of pairwise correlation. This has key implications not only > for reverse engineering but also for other methods, such as hierarchical > clustering, relying on accurate measurements of pairwise expression > profile correlation. We propose an alternative implementation to > eliminate such side effect". > > I've checked the papers that reference this work, but no one is about > the improvement of GCRMA. Does anyone know if, after this paper was > published, GCRMA was fixed? > > Thanks, > Javier > > _______________________________________________ > 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 -- ------------------------------------ Zhijin (Jean) Wu Assistant Professor of Biostatistics Brown University, Box G-S121 Providence, RI 02912 Tel: 401 863 1230 Fax: 401 863 9182 http://www.stat.brown.edu/zwu