DEFOR: depth- and frequency-based somatic copy number alteration detector

He Zhang; Xiaowei Zhan; James Brugarolas; Yang Xie

doi:10.1093/bioinformatics/btz170

DEFOR: depth- and frequency-based somatic copy number alteration detector

Bioinformatics. 2019 Oct 1;35(19):3824-3825. doi: 10.1093/bioinformatics/btz170.

Authors

He Zhang¹, Xiaowei Zhan¹, James Brugarolas², Yang Xie^{1

2}

Affiliations

¹ Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
² Department of Internal Medicine and Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.

Abstract

Motivation: Detection of somatic copy number alterations (SCNAs) using high-throughput sequencing has become popular because of rapid developments in sequencing technology. Existing methods do not perform well in calling SCNAs for the unstable tumor genomes.

Results: We developed a new method, DEFOR, to detect SCNAs in tumor samples from exome-sequencing data. The evaluation showed that DEFOR has a higher accuracy for SCNA detection from exome sequencing compared with the five existing tools. This advantage is especially apparent in unstable tumor genomes with a large proportion of SCNAs.

Availability and implementation: DEFOR is available at https://github.com/drzh/defor.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
DNA Copy Number Variations*
Exome
Exome Sequencing
High-Throughput Nucleotide Sequencing
Software

Grants and funding

P50 CA196516/CA/NCI NIH HHS/United States