Ultra-Fast Next Generation Human Genome Sequencing Data Processing Using DRAGENTM Bio-IT Processor for Precision Medicine
| Autor: | Sung Hoon Lee, Reena Garg, Kichan Lee, Hyuk Jung Kwon, Seon Young Yun, Yoon Hee Kim, Amit Goyal, Min Seob Lee |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Computer science business.industry Pipeline (computing) Real-time computing Big data Genomics Bioinformatics Precision medicine Bottleneck 03 medical and health sciences 030104 developmental biology 0302 clinical medicine Workflow 030220 oncology & carcinogenesis Human genome business Throughput (business) |
| Zdroj: | Open Journal of Genetics. :9-19 |
| ISSN: | 2162-4461 2162-4453 |
| DOI: | 10.4236/ojgen.2017.71002 |
| Popis: | Slow speed of the Next-Generation sequencing data analysis, compared to the latest high throughput sequencers such as HiSeq X system, using the current industry standard genome analysis pipeline, has been the major factor of data backlog which limits the real-time use of genomic data for precision medicine. This study demonstrates the DRAGEN Bio-IT Processor as a potential candidate to remove the “Big Data Bottleneck”. DRAGENTM accomplished the variant calling, for ~40× coverage WGS data in as low as ~30 minutes using a single command, achieving the over 50-fold data analysis speed while maintaining the similar or better variant calling accuracy than the standard GATK Best Practices workflow. This systematic comparison provides the faster and efficient NGS data analysis alternative to NGS-based healthcare industries and research institutes to meet the requirement for precision medicine based healthcare. |
| Databáze: | OpenAIRE |
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