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PASA: Identifying More Credible Structural Variants of Hedou12

  • Huiqiang Jia
  • Haichao Wei
  • Daming Zhu
  • Ruizhi Wang
  • Haodi Feng
  • Xiangzhong Feng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10954)

Abstract

In this paper, we devote to find structural variants including deletions, insertions, and inversions which occur in Hedou12 genome in constrast to Williams82 genome. To find as many as possible potential structural variants, we try to develop new principles to detect discordant and split read map sets supporting structural variants. Aiming to enhance the precision of structural variant detection, we propose two new sequencing characteristic based models, which use the sequencing parameters of Hedou12 paired-end reads, as well as the parameters for Hedou12 paired-end reads to be aligned onto Williams82, to evaluate the probability a potential structural variant can occur in. To remove those false members from the potential structural variants, we propose a integer linear program to describe formally on which potential structural variants it should accept to achieve as high as possible a probability summation, whose solution can help predict more credible structural variants. The feasibility and precision of our algorithm are verified by comparing with DELLY version 0.5.8 and LUMPY version 0.2.2.3. The software is available for download at https://pan.baidu.com/s/1rasmtti.

Keywords

Algorithm Deletion Insertion Inversion Structural variant 

Notes

Acknowledgment

This paper is supported by National natural science foundation of China, No. 61472222, 61732009, 61672325, 61761136017.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Huiqiang Jia
    • 1
  • Haichao Wei
    • 2
  • Daming Zhu
    • 1
  • Ruizhi Wang
    • 1
  • Haodi Feng
    • 1
  • Xiangzhong Feng
    • 2
  1. 1.School of Computer Science and TechnologyShandong UniversityJinanChina
  2. 2.Key Laboratory of Soybean Molecular Design Breeding, Northeast Institute of Geography and AgroecologyChinese Academy of SciencesChangchunChina

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