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

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)3824-3825
Number of pages2
JournalBioinformatics
Volume35
Issue number19
DOIs
StatePublished - Oct 1 2019

Fingerprint

Exome
Tumors
Sequencing
Detector
Detectors
Genes
Tumor
Genome
Neoplasms
Bioinformatics
Computational Biology
Unstable
Throughput
Availability
Technology
High Throughput
High Accuracy
Proportion
Evaluation

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Cite this

DEFOR : Depth- and frequency-based somatic copy number alteration detector. / Zhang, He; Zhan, Xiaowei; Brugarolas, James; Xie, Yang.

In: Bioinformatics, Vol. 35, No. 19, 01.10.2019, p. 3824-3825.

Research output: Contribution to journalArticle

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