tailieunhanh - Báo cáo y học: "An optimization framework for unsupervised identification of rare copy number variation from SNP array data."

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Wertheim cung cấp cho các bạn kiến thức về ngành y đề tài: An optimization framework for unsupervised identification of rare copy number variation from SNP array data. | Method Open Access An optimization framework for unsupervised identification of rare copy number variation from SNP array . data Gokhan Yavas Mehmet Koyuturk Meral Ozsoyoglu Meetha P Gould and Thomas LaFramboise Addresses Department of Electrical Engineering and Computer Science Case Western Reserve University 10900 Euclid Avenue Cleveland OH 44106 USA. Center for Proteomics and Bioinformatics Case Western Reserve University 10900 Euclid Avenue Cleveland OH 44106 USA. Department of Genetics Case Western Reserve University 10900 Euclid Avenue Cleveland OH 44106 USA. Genomic Medicine Institute Lerner Research Institute Cleveland Clinic Foundation 9500 Euclid Avenue Cleveland OH 44195 USA. Correspondence Thomas LaFramboise. Email Published 23 October 2009 Genome Biology 2009 10 R119 doi gb-2009-l0-l0-rll9 The electronic version of this article is the complete one and can be found online at http 2009 10 10 R119 Received 21 September 2009 Accepted 23 October 2009 2009 Yavaạ et al. licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Copy number variants CNVs have roles in human disease and DNA microarrays are important tools for identifying them. In this paper we frame CNV identification as an objective function optimization problem. We apply our method to data from hundreds of samples and demonstrate its ability to detect CNVs at a high level of sensitivity without sacrificing specificity. Its performance compares favorably with currently available methods and it reveals previously unreported gains and losses. Background Identifying DNA variants that contribute to disease is a central aim in human genetics research. Pinpointing these causal loci requires the ability to .