期刊
NUCLEIC ACIDS RESEARCH
卷 39, 期 -, 页码 W567-W575出版社
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkr506
关键词
-
资金
- Fudan University (Ministry of Education of China)
- Rijk Zwaan (Netherlands)
- CAS [Y064021BJ1, 0869011BJ5]
Mining genetic variation from personal genomes is a crucial step towards investigating the relationship between genotype and phenotype. However, compared to the detection of SNPs and small indels, characterizing large and particularly complex structural variation is much more difficult and less intuitive. In this article, we present a new scheme (inGAP-sv) to detect and visualize structural variation from paired-end mapping data. Under this scheme, abnormally mapped read pairs are clustered based on the location of a gap signature. Several important features, including local depth of coverage, mapping quality and associated tandem repeat, are used to evaluate the quality of predicted structural variation. Compared with other approaches, it can detect many more large insertions and complex variants with lower false discovery rate. Moreover, inGAP-sv, written in Java programming language, provides a user-friendly interface and can be performed in multiple operating systems. It can be freely accessed at http://ingap.sourceforge.net/.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据