An Evaluation of Copy Number Variation Detection Tools from Whole‐Exome Sequencing Data. Issue 7 (1st May 2014)

• Record Type: Journal Article
• Authors: Tan, Renjie; Wang, Yadong; Kleinstein, Sarah E.; Liu, Yongzhuang; Zhu, Xiaolin; Guo, Hongzhe; Jiang, Qinghua; Allen, Andrew S.; Zhu, Mingfu
• Is Part Of: Human mutation. Volume 35:Issue 7(2014:Jul.)
• Page Start: 899
• Page End: 907
• Publication Date: 2014-05-01
• Subjects: Human chromosome abnormalities -- Periodicals; Mutation (Biology) -- Periodicals; 616.04205
• DOI: 10.1002/humu.22537
• Languages: English
• ISSNs: 1059-7794

Abstract

<abstract abstract-type="graphical" xml:lang="en" id="humu22537-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p>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. In this study, we provided a comprehensive and objective comparison of several well‐known detection tools designed for WES data. We found that the sensitive and accurate detection of CNVs in WES data remains challenging. Our evaluation results will assist researchers in choosing the most suitable tools for their research needs. <boxed-text content-type="graphic" position="anchor" orientation="portrait"><graphic position="anchor" mimetype="image" xlink:href="ark:/27927/pghmgm4wc9" orientation="portrait" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink" /></boxed-text></p> </abstract>