rSW-seq: Algorithm for detection of copy number alterations in deep sequencing data

BMC Bioinformatics

Research Article

Tae-Min Kim¹  Ruibin Xi¹  Lovelace J Luquette¹  Peter J Park² 

[1] Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck St, 02115, Boston, Massachusetts, USA;Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck St, 02115, Boston, Massachusetts, USA;Department of Medicine, Brigham and Women's Hospital, 77 Avenue Louis Pasteur, 02115, Boston, Massachusetts, USA;Harvard-MIT Health Sciences and Technology Informatics Program at Children's Hospital, 300 Longwood Ave., 02115, Boston, Massachusetts, USA;

关键词: Homozygous Deletion;    Copy Number Change;    Copy Number Alteration;    Copy Number Gain;    Normal Genome;   

DOI  :  10.1186/1471-2105-11-432

 received in 2009-12-31, accepted in 2010-08-18,  发布年份 2010

来源: Springer

【 摘 要 】

BackgroundRecent advances in sequencing technologies have enabled generation of large-scale genome sequencing data. These data can be used to characterize a variety of genomic features, including the DNA copy number profile of a cancer genome. A robust and reliable method for screening chromosomal alterations would allow a detailed characterization of the cancer genome with unprecedented accuracy.ResultsWe develop a method for identification of copy number alterations in a tumor genome compared to its matched control, based on application of Smith-Waterman algorithm to single-end sequencing data. In a performance test with simulated data, our algorithm shows >90% sensitivity and >90% precision in detecting a single copy number change that contains approximately 500 reads for the normal sample. With 100-bp reads, this corresponds to a ~50 kb region for 1X genome coverage of the human genome. We further refine the algorithm to develop rSW-seq, (recursive Smith-Waterman-seq) to identify alterations in a complex configuration, which are commonly observed in the human cancer genome. To validate our approach, we compare our algorithm with an existing algorithm using simulated and publicly available datasets. We also compare the sequencing-based profiles to microarray-based results.ConclusionWe propose rSW-seq as an efficient method for detecting copy number changes in the tumor genome.

【 授权许可】

Unknown   
© Kim et al; licensee BioMed Central Ltd. 2010. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.