title: Sprites: detection of deletions from sequencing data by re-aligning split reads.
abstract: Advances of next generation sequencing technologies and availability of short read data enable the detection of structural variations (SVs). Deletions, an important type of SVs, have been suggested in association with genetic diseases. There are three types of deletions: blunt deletions, deletions with microhomologies and deletions with microsinsertions. The last two types are very common in the human genome, but they pose difficulty for the detection. Furthermore, finding deletions from sequencing data remains challenging. It is highly appealing to develop sensitive and accurate methods to detect deletions from sequencing data, especially deletions with microhomology and deletions with microinsertion.
  
  
  
  We present a novel method called Sprites (SPlit Read re-alIgnment To dEtect Structural variants) which finds deletions from sequencing data. It aligns a whole soft-clipping read rather than its clipped part to the target sequence, a segment of the reference which is determined by spanning reads, in order to find the longest prefix or suffix of the read that has a match in the target sequence. This alignment aims to solve the problem of deletions with microhomologies and deletions with microinsertions. Using both simulated and real data we show that Sprites performs better on detecting deletions compared with other current methods in terms of F-score.
  
  
  
  Sprites is open source software and freely available at https://github.com/zhangzhen/sprites
  
  
  
  jxwang@mail.csu.edu.cnSupplementary data: Supplementary data are available at Bioinformatics online.
authors.affiliation: School of Information Science and Engineering, Central South University, Changsha, 410083, China, College of Information and Communication Engineering, Hunan Institute of Science and Technology, Yueyang, 414006, China.
authors.forename: Zhen
authors.initials: Z
authors.lastname: Zhang
authors.affiliation: School of Information Science and Engineering, Central South University, Changsha, 410083, China.
authors.forename: Jianxin
authors.initials: J
authors.lastname: Wang
authors.affiliation: School of Information Science and Engineering, Central South University, Changsha, 410083, China.
authors.forename: Junwei
authors.initials: J
authors.lastname: Luo
authors.affiliation: School of Information Science and Engineering, Central South University, Changsha, 410083, China.
authors.forename: Xiaojun
authors.initials: X
authors.lastname: Ding
authors.affiliation: School of Information Science and Engineering, Central South University, Changsha, 410083, China.
authors.forename: Jiancheng
authors.initials: J
authors.lastname: Zhong
authors.affiliation: Department of Molecular Physiology & Biophysics, Baylor College of Medicine, Houston, TX 77030, USA.
authors.forename: Jun
authors.initials: J
authors.lastname: Wang
authors.affiliation: Department of Mechanical Engineering and Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK S7N 5A9, Canada and.
authors.forename: Fang-Xiang
authors.initials: FX
authors.lastname: Wu
authors.affiliation: Department of Computer Science, Georgia State University, Atlanta, GA 30302-4110, USA.
authors.forename: Yi
authors.initials: Y
authors.lastname: Pan
mesh_terms: D015894:Genome, Human; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D017384:Sequence Deletion; D012984:Software