tailieunhanh - báo cáo hóa học:" Research Article A Bayesian Analysis for Identifying DNA Copy Number Variations Using a Compound Poisson Process"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Bayesian Analysis for Identifying DNA Copy Number Variations Using a Compound Poisson Process | Hindawi Publishing Corporation EURASIP Journal on Bioinformatics and Systems Biology Volume 2010 Article ID 268513 10 pages doi 2010 268513 Research Article A Bayesian Analysis for Identifying DNA Copy Number Variations Using a Compound Poisson Process Jie Chen 1 Ayten Yigiter 2 Yu-Ping Wang 3 and Hong-Wen Deng4 1 Department of Mathematics and Statistics University of Missouri-Kansas City Kansas City MO 64110 USA 2 Department of Statistics Hacettepe University 06800 Beytepe-Ankara Turkey 3Biomedical Engineering Department Tulane University New Orleans LA 70118 USA 4 Departments of Orthopedic Surgery and Basic Medical Sciences School of Medicine University of Missouri-Kansas City Kansas City Mo 64108 USA Correspondence should be addressed to Jie Chen chenj@ Received 3 May 2010 Revised 29 July 2010 Accepted 6 August 2010 Academic Editor Yue Joseph Wang Copyright 2010 Jie Chen et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. To study chromosomal aberrations that may lead to cancer formation or genetic diseases the array-based Comparative Genomic Hybridization aCGH technique is often used for detecting DNA copy number variants CNVs . Various methods have been developed for gaining CNVs information based on aCGH data. However most of these methods make use of the log-intensity ratios in aCGH data without taking advantage of other information such as the DNA probe . biomarker positions distances contained in the data. Motivated by the specific features of aCGH data we developed a novel method that takes into account the estimation of a change point or locus of the CNV in aCGH data with its associated biomarker position on the chromosome using a compound Poisson process. We used a Bayesian approach to derive the posterior probability for the estimation of the CNV locus. To detect loci of