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CONSERTING: integrating copy number analysis with structural variation detection

ABSTRACT: We developed Copy Number Segmentation by Regression Tree in Next Generation Sequencing (CONSERTING), a novel algorithm for detecting somatic copy number alteration (CNA) using whole-genome sequencing (WGS) data. CONSERTING performs iterative analysis of segmentation by read depth change and localized structural variation detection to achieve high accuracy and sensitivity. Analysis of 43 pediatric and adult cancer genomes revealed novel oncogenic CNAs, complex re-arrangements and subclonal CNAs missed by alternative approaches. This study contains all data for "CONSERTING: an accurate method for detecting somatic DNA copy number alterations in whole genome sequencing data", which was previously split between EGAS00001001202 and EGAS00001001050.

PROVIDER: EGAS00001001202 | EGA |

REPOSITORIES: EGA

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CONSERTING: integrating copy-number analysis with structural-variation detection.

Chen Xiang X Gupta Pankaj P Wang Jianmin J Nakitandwe Joy J Roberts Kathryn K Dalton James D JD Parker Matthew M Patel Samir S Holmfeldt Linda L Payne Debbie D Easton John J Ma Jing J Rusch Michael M Wu Gang G Patel Aman A Baker Suzanne J SJ Dyer Michael A MA Shurtleff Sheila S Espy Stephen S Pounds Stanley S Downing James R JR Ellison David W DW Mullighan Charles G CG Zhang Jinghui J

Nature methods 20150504 6

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 re ...[more]

PMID: 25938371

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