MOTIVATION: Affymetrix microarrays are widely used to measure global expression of mRNA transcripts. That technology is based on the concept of a probe set. Individual probes within a probe set were originally designated by Affymetrix to hybridize with the same unique mRNA transcript. Because of increasing accuracy in knowledge of genomic sequences, however, a substantial number of the manufacturer's original probe groupings and mappings are now known to be inaccurate and must be corrected. Otherwise, analysis and interpretation of an Affymetrix microarray experiment will be in error. RESULTS: AffyProbeMiner is a computationally efficient platform-independent tool that uses all RefSeq mature RNA protein coding transcripts and validated complete coding sequences in GenBank to (1) regroup the individual probes into consistent probe sets and (2) remap the probe sets to the correct sets of mRNA transcripts. The individual probes are grouped into probe sets that are 'transcript-consistent' in that they hybridize to the same mRNA transcript (or transcripts) and, therefore, measure the same entity (or entities). About 65.6% of the probe sets on the HG-U133A chip were affected by the remapping. Pre-computed regrouped and remapped probe sets for many Affymetrix microarrays are made freely available at the AffyProbeMiner web site. Alternatively, we provide a web service that enables the user to perform the remapping for any type of short-oligo commercial or custom array that has an Affymetrix-format Chip Definition File (CDF). Important features that differentiate AffyProbeMiner from other approaches are flexibility in the handling of splice variants, computational efficiency, extensibility, customizability and user-friendliness of the interface. AVAILABILITY: The web interface and software (GPL open source license), are publicly-accessible at http://discover.nci.nih.gov/affyprobeminer.
MOTIVATION: Affymetrix microarrays are widely used to measure global expression of mRNA transcripts. That technology is based on the concept of a probe set. Individual probes within a probe set were originally designated by Affymetrix to hybridize with the same unique mRNA transcript. Because of increasing accuracy in knowledge of genomic sequences, however, a substantial number of the manufacturer's original probe groupings and mappings are now known to be inaccurate and must be corrected. Otherwise, analysis and interpretation of an Affymetrix microarray experiment will be in error. RESULTS: AffyProbeMiner is a computationally efficient platform-independent tool that uses all RefSeq mature RNA protein coding transcripts and validated complete coding sequences in GenBank to (1) regroup the individual probes into consistent probe sets and (2) remap the probe sets to the correct sets of mRNA transcripts. The individual probes are grouped into probe sets that are 'transcript-consistent' in that they hybridize to the same mRNA transcript (or transcripts) and, therefore, measure the same entity (or entities). About 65.6% of the probe sets on the HG-U133A chip were affected by the remapping. Pre-computed regrouped and remapped probe sets for many Affymetrix microarrays are made freely available at the AffyProbeMiner web site. Alternatively, we provide a web service that enables the user to perform the remapping for any type of short-oligo commercial or custom array that has an Affymetrix-format Chip Definition File (CDF). Important features that differentiate AffyProbeMiner from other approaches are flexibility in the handling of splice variants, computational efficiency, extensibility, customizability and user-friendliness of the interface. AVAILABILITY: The web interface and software (GPL open source license), are publicly-accessible at http://discover.nci.nih.gov/affyprobeminer.
Authors: Jeffrey D Allen; Siling Wang; Min Chen; Luc Girard; John D Minna; Yang Xie; Guanghua Xiao Journal: Brief Bioinform Date: 2011-12-23 Impact factor: 11.622
Authors: David Kozono; Jie Li; Masayuki Nitta; Oltea Sampetrean; David Gonda; Deepa S Kushwaha; Dmitry Merzon; Valya Ramakrishnan; Shan Zhu; Kaya Zhu; Hiroko Matsui; Olivier Harismendy; Wei Hua; Ying Mao; Chang-Hyuk Kwon; Hideyuki Saya; Ichiro Nakano; Donald P Pizzo; Scott R VandenBerg; Clark C Chen Journal: Proc Natl Acad Sci U S A Date: 2015-07-09 Impact factor: 11.205
Authors: Roel G W Verhaak; Pablo Tamayo; Ji-Yeon Yang; Diana Hubbard; Hailei Zhang; Chad J Creighton; Sian Fereday; Michael Lawrence; Scott L Carter; Craig H Mermel; Aleksandar D Kostic; Dariush Etemadmoghadam; Gordon Saksena; Kristian Cibulskis; Sekhar Duraisamy; Keren Levanon; Carrie Sougnez; Aviad Tsherniak; Sebastian Gomez; Robert Onofrio; Stacey Gabriel; Lynda Chin; Nianxiang Zhang; Paul T Spellman; Yiqun Zhang; Rehan Akbani; Katherine A Hoadley; Ari Kahn; Martin Köbel; David Huntsman; Robert A Soslow; Anna Defazio; Michael J Birrer; Joe W Gray; John N Weinstein; David D Bowtell; Ronny Drapkin; Jill P Mesirov; Gad Getz; Douglas A Levine; Matthew Meyerson Journal: J Clin Invest Date: 2012-12-21 Impact factor: 14.808
Authors: Adam J Bass; Hideo Watanabe; Craig H Mermel; Soyoung Yu; Sven Perner; Roel G Verhaak; So Young Kim; Leslie Wardwell; Pablo Tamayo; Irit Gat-Viks; Alex H Ramos; Michele S Woo; Barbara A Weir; Gad Getz; Rameen Beroukhim; Michael O'Kelly; Amit Dutt; Orit Rozenblatt-Rosen; Piotr Dziunycz; Justin Komisarof; Lucian R Chirieac; Christopher J Lafargue; Veit Scheble; Theresia Wilbertz; Changqing Ma; Shilpa Rao; Hiroshi Nakagawa; Douglas B Stairs; Lin Lin; Thomas J Giordano; Patrick Wagner; John D Minna; Adi F Gazdar; Chang Qi Zhu; Marcia S Brose; Ivan Cecconello; Ulysses Ribeiro; Suely K Marie; Olav Dahl; Ramesh A Shivdasani; Ming-Sound Tsao; Mark A Rubin; Kwok K Wong; Aviv Regev; William C Hahn; David G Beer; Anil K Rustgi; Matthew Meyerson Journal: Nat Genet Date: 2009-10-04 Impact factor: 38.330
Authors: Joanna Boros; Amanda O'Donnell; Ian J Donaldson; Aneta Kasza; Leo Zeef; Andrew D Sharrocks Journal: Nucleic Acids Res Date: 2009-12 Impact factor: 16.971
Authors: Richard D Pearson; Xuejun Liu; Guido Sanguinetti; Marta Milo; Neil D Lawrence; Magnus Rattray Journal: BMC Bioinformatics Date: 2009-07-09 Impact factor: 3.169