Abstract
In order to improve the accuracy of indel detection, micro-assembly is used in multiple variant callers, such as the GATK HaplotypeCaller to reassemble reads in a specific region of the genome. Assembly is a computationally intensive process that causes runtime bottlenecks. In this paper, we propose a GPU-based de Bruijn graph construction algorithm for micro-assembly in the GATK HaplotypeCaller to improve its performance. Various synthetic datasets are used to compare the performance of the GPU-based de Bruijn graph construction implementation with the software-only baseline, which achieves a speedup of up to 3x. An experiment using two human genome datasets is used to evaluate the performance shows a speedup of up to 2.66x.
Original language | English |
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Title of host publication | Proceedings - 2018 IEEE 18th annual IEEE International Conference on BioInformatics and BioEngineering (BIBE 2018) |
Editors | Nikolaos G. Bourbakis, Despina Kavraki |
Place of Publication | Piscataway, NJ, USA |
Publisher | IEEE |
Pages | 67-72 |
Number of pages | 6 |
ISBN (Electronic) | 978-153866216-8 |
DOIs | |
Publication status | Published - 2018 |
Event | BIBE 2018 : 18th International Conference on Bioinformatics and Bioengineering - Taichung, Taiwan Duration: 6 Dec 2018 → 6 Dec 2018 |
Conference
Conference | BIBE 2018 : 18th International Conference on Bioinformatics and Bioengineering |
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Country/Territory | Taiwan |
City | Taichung |
Period | 6/12/18 → 6/12/18 |
Keywords
- De Bruijn graph construction
- GPU acceleration
- Micro-assembly
- Repeat k-mers