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An Improved Detection Algorithm for Indel Variations Based on High-throughput Sequencing Reads

文献类型： 外文期刊

作者： Yang, Hai 1 ; Zhu, Daming 1 ; Zhang, Yanwei 2 ;

作者机构： 1.Shandong Univ, Sch Comp Sci & Technol, Qingdao 266237, Shandong, Peoples R China

2.Shandong Acad Agr Sci, Crop Res Inst, Jinan 250131, Shandong, Peoples R China

关键词： Indel Variation; Paired-end Read; Split Read; Read Depth; Dynamic Programming

期刊名称：INVESTIGACION CLINICA （ 影响因子：0.683； 五年影响因子：0.59 ）

ISSN： 0535-5133

年卷期： 2018 年 59 卷 3 期

页码：

收录情况： SCI

摘要： Indel variations include two types of common variations in the genome, insertion and deletion. Indel variations have been verified to be related to phenotypic differences and diseases of individuals. However, almost of current detection algorithms have their limitations in detecting indels. Thus, it is very significant to improve the detection algorithm for indel. In this paper, an improved detection algorithm for indel based on high-throughput sequencing reads, which is named IDAI has been proposed. The IDAI algorithm clusters the discordant paired-end reads and split reads firstly, and then determines the type of indel variations using the discordant paired-end reads. Subsequently, the breakpoints can further determine at single-base resolution by utilizing the split reads. Furthermore, the read depth is also used to detect more deletion and improve higher confidence in the deletion detection. Finally, the experimental results show that our improved algorithm can detect indels both in the coding sequence region and the whole genome respectively, which has higher sensitivity and applicability in detecting indel variations than most of current algorithms.

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