Exploiting in-memory systems for gnomic data analysis.
Conference item
Authors | Shah, Zeeshan Ali, El-Kalioby, Mohamed, Faquih, Tariq, Shokrof, Moustafa, Subhani, Shazia, Alnakhli, Yasser, Aljafar, Hussain, Anjum, Ashiq and Abouelhoda, Mohamed |
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Abstract | With the increasing adoption of next generation sequencing technology in the medical practice, there is an increasing demand for faster data processing to gain immediate insights from the patient’s genome. Due to the extensive amount of genomic information and its big data nature, data processing takes long time and delays are often experienced. In this paper, we show how to exploit in-memory platforms for big genomic data analysis, with focus on the variant analysis workflow. We will determine where different in-memory techniques are used in the workflow and explore different memory-based strategies to speed up the analysis. Our experiments show promising results and encourage further research in this area, especially with the rapid advancement in memory and SSD technologies. |
Keywords | Bioinformatics; Big data; In memory processing; Next generation sequencing |
Year | 2018 |
Publisher | Springer |
Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-319-78723-7_35 |
Web address (URL) | http://hdl.handle.net/10545/622730 |
hdl:10545/622730 | |
ISBN | 9783319787220 |
File | File Access Level Open |
Publication dates | 28 Mar 2018 |
Publication process dates | |
Deposited | 22 May 2018, 13:24 |
Contributors | King Faisal Specialist Hospital and Research Center, King Abdulaziz City for Science and Technology and University of Derby |
https://repository.derby.ac.uk/item/9525y/exploiting-in-memory-systems-for-gnomic-data-analysis
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