Literature DB >> 30596895

ACE: absolute copy number estimation from low-coverage whole-genome sequencing data.

Jos B Poell1,2, Matias Mendeville2, Daoud Sie2, Arjen Brink1, Ruud H Brakenhoff1, Bauke Ylstra2.   

Abstract

SUMMARY: Chromosomal copy number aberrations can be efficiently detected and quantified using low-coverage whole-genome sequencing, but analysis is hampered by the lack of knowledge on absolute DNA copy numbers and tumor purity. Here, we describe an analytical tool for Absolute Copy number Estimation, ACE, which scales relative copy number signals from chromosomal segments to optimally fit absolute copy numbers, without the need for additional genetic information, such as SNP data. In doing so, ACE derives an estimate of tumor purity as well. ACE facilitates analysis of large numbers of samples, while maintaining the flexibility to customize models and generate output of single samples.
AVAILABILITY AND IMPLEMENTATION: ACE is freely available via www.bioconductor.org and at www.github.com/tgac-vumc/ACE. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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Year:  2019        PMID: 30596895     DOI: 10.1093/bioinformatics/bty1055

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  10 in total

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  10 in total

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