title: An evaluation of copy number variation detection tools from whole-exome sequencing data.
abstract: Copy number variation (CNV) has been found to play an important role in human disease. Next-generation sequencing technology, including whole-genome sequencing (WGS) and whole-exome sequencing (WES), has become a primary strategy for studying the genetic basis of human disease. Several CNV calling tools have recently been developed on the basis of WES data. However, the comparative performance of these tools using real data remains unclear. An objective evaluation study of these tools in practical research situations would be beneficial. Here, we evaluated four well-known WES-based CNV detection tools (XHMM, CoNIFER, ExomeDepth, and CONTRA) using real data generated in house. After evaluation using six metrics, we found that the sensitive and accurate detection of CNVs in WES data remains challenging despite the many algorithms available. Each algorithm has its own strengths and weaknesses. None of the exome-based CNV calling methods performed well in all situations; in particular, compared with CNVs identified from high coverage WGS data from the same samples, all tools suffered from limited power. Our evaluation provides a comprehensive and objective comparison of several well-known detection tools designed for WES data, which will assist researchers in choosing the most suitable tools for their research needs.
authors.affiliation: Center for Biomedical Informatics, School of Computer Science and Technology, Harbin Institute Technology, Harbin, Heilongjiang, China; Center for Human Genome Variation, Duke University School of Medicine, Durham, North Carolina.
authors.forename: Renjie
authors.initials: R
authors.lastname: Tan
authors.forename: Yadong
authors.initials: Y
authors.lastname: Wang
authors.forename: Sarah E
authors.initials: SE
authors.lastname: Kleinstein
authors.forename: Yongzhuang
authors.initials: Y
authors.lastname: Liu
authors.forename: Xiaolin
authors.initials: X
authors.lastname: Zhu
authors.forename: Hongzhe
authors.initials: H
authors.lastname: Guo
authors.forename: Qinghua
authors.initials: Q
authors.lastname: Jiang
authors.forename: Andrew S
authors.initials: AS
authors.lastname: Allen
authors.forename: Mingfu
authors.initials: M
authors.lastname: Zhu
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D056915:DNA Copy Number Variations; D066264:Datasets as Topic; D059472:Exome; D023281:Genomics / Q000379:methods; D006579:Heterozygote; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D020641:Polymorphism, Single Nucleotide; D012680:Sensitivity and Specificity; D017384:Sequence Deletion; D012984:Software
keywords: copy number variation; evaluation studies; whole-exome sequencing; whole-genome sequencing