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Bioinformatics. 2018 Dec 28. doi: 10.1093/bioinformatics/bty1055. [Epub ahead of print]

ACE: Absolute Copy number Estimation from low-coverage whole-genome sequencing data.

Author information

1
Otolaryngology/Head and Neck Surgery, Amsterdam UMC, Vrije Universiteit Amsterdam.
2
Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam the Netherlands.

Abstract

Summary:

Chromosomal copy number aberrations can be efficiently detected and quantified using low-coverage whole-genome sequencing (lcWGS), 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 methods and data are available at Bioinformatics online. Documentation, example data, and a vignette, are included in the R package of ACE.

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