Integrated Sequence Assembly-based Approach for Calling Genomic Long Insertion
- 10.2991/amcce-17.2017.147How to use a DOI?
- high-throughput sequencing; long insertions; soft-cilpped reads; sequence assembly
With the application and development of high-throughput sequencing technology, the detection methods of structural variants based on sequencing have emerged. However, since the high-throughput sequencing reads is relatively short compared to the previous sequencing reads, it is difficult to detect long insertion. Although assembly-based approach can solve long insertion, the computational resources used for assembly are too complex, resulting in poor results of assembly and final detection. To this end, ISALins was proposed, firstly the initial results of three different detection tools were merged; then high quality soft-cilpped reads and unmapped reads which is the set of most probable reads containing information of insertion were analyzed and extracted around the initial suspect SV breakpoints; finally these reads were assembled using assembly tool based on De Bruijn Graphs. By experimenting on both simulated and real data, we found that the method was superior to the single tool in detecting precision and sensitivity. Compared with the direct combination of call results of multiple tools, in ensuring detection sensitivity of the premise, ISALins significantly improved the detection accuracy.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Lu Ye AU - JingYang Gao PY - 2017/03 DA - 2017/03 TI - Integrated Sequence Assembly-based Approach for Calling Genomic Long Insertion BT - Proceedings of the 2017 2nd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2017) PB - Atlantis Press SP - 831 EP - 836 SN - 2352-5401 UR - https://doi.org/10.2991/amcce-17.2017.147 DO - 10.2991/amcce-17.2017.147 ID - Ye2017/03 ER -