Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/113691
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Type: Journal article
Title: CONSERTING: integrating copy-number analysis with structural-variation detection
Author: Chen, X.
Gupta, P.
Wang, J.
Nakitandwe, J.
Roberts, K.
Dalton, J.D.
Parker, M.
Patel, S.
Holmfeldt, L.
Payne, D.
Easton, J.
Ma, J.
Rusch, M.
Wu, G.
Patel, A.
Baker, S.J.
Dyer, M.A.
Shurtleff, S.
Espy, S.
Pounds, S.
et al.
Citation: Nature Methods, 2015; 12(6):527-530
Publisher: Nature Publishing Group
Issue Date: 2015
ISSN: 1548-7091
1548-7105
Statement of
Responsibility: 
Xiang Chen, Pankaj Gupta, Jianmin Wang, Joy Nakitandwe, Kathryn Roberts, James D Dalton, Matthew Parker, Samir Patel, Linda Holmfeldt, Debbie Payne, John Easton, Jing Ma, Michael Rusch, Gang Wu, Aman Patel, Suzanne J Baker, Michael A Dyer, Sheila Shurtleff, Stephen Espy, Stanley Pounds, James R Downing, David W Ellison, Charles G Mullighan, Jinghui Zhang
Abstract: We developed Copy Number Segmentation by Regression Tree in Next Generation Sequencing (CONSERTING), an algorithm for detecting somatic copy-number alteration (CNA) using whole-genome sequencing (WGS) data. CONSERTING performs iterative analysis of segmentation on the basis of changes in read depth and the detection of localized structural variations, with high accuracy and sensitivity. Analysis of 43 cancer genomes from both pediatric and adult patients revealed novel oncogenic CNAs, complex rearrangements and subclonal CNAs missed by alternative approaches.
Keywords: Computational Biology
Rights: © 2015 Nature America, Inc. All rights reserved.
DOI: 10.1038/nmeth.3394
Published version: http://dx.doi.org/10.1038/nmeth.3394
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