Sprites: detection of deletions from sequencing data by re-aligning split reads
Sprites: detection of deletions from sequencing data by re-aligning split reads
复制标题
Sprites：通过重新对齐分割读数来检测测序数据中的删除
DOI：
10.1093/bioinformatics/btw053
复制
发表时间：
2016
期刊：
影响因子：
5.8
通讯作者：
Pan Yi
中科院分区：
文献类型：
--
作者：
Zhang Zhen;Wang Jianxin;Luo Junwei;Ding Xiaojun;Zhong Jiancheng;Wang Jun;Wu Fang-Xiang;Pan Yi
动机
下一代测序技术的进步和短读段数据的可用性使得能够检测结构变异（SV）。缺失是SV的一种重要类型，已被认为与遗传疾病有关。有三种类型的缺失：钝性缺失、具有微同源性的缺失和具有微插入的缺失。后两种类型在人类基因组中非常常见，但它们给检测带来了困难。此外，从测序数据中发现缺失仍然具有挑战性。因此，发展一种灵敏、准确的方法来检测测序数据中的缺失，特别是微同源性缺失和微插入缺失，具有很强的吸引力。
结果
我们提出了一种称为Sprites（SPlit Read re-alIgnment To dEtect Structural variants）的新方法，该方法从测序数据中发现缺失。它将整个软剪切读段而不是其剪切部分与靶序列（通过跨越读段确定的参考片段）进行比对，以找到在靶序列中具有匹配的读段的最长前缀或后缀。该比对旨在解决微同源性缺失和微插入缺失的问题。使用模拟和真实的数据，我们表明，Sprites执行更好的检测删除相比，目前的其他方法的F-分数。
可用性和执行
Sprites是开源软件，可在https://github.com/zhangzhen/sprites上免费获得
接触
jxwang@mail.csu.edu. cn补充数据：补充数据可在Bioinformatics online获得。
MOTIVATION
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.
RESULTS
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.
AVAILABILITY AND IMPLEMENTATION
Sprites is open source software and freely available at https://github.com/zhangzhen/sprites
CONTACT
jxwang@mail.csu.edu.cnSupplementary data: Supplementary data are available at Bioinformatics online.