寻找结直肠癌中基因-基因相互作用:使用HPC克服计算障碍

F. Scharinger, Fiona J L Reid, Paul Graham, A. Trew, A. Tenesa, S. Farrington, H. Campbell, M. Dunlop
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引用次数: 2

摘要

英国国家癌症登记数据显示,每年约有35000人被诊断患有结肠直肠癌(大肠癌和直肠癌),其中16000人死于该疾病。爱丁堡大学的结肠癌遗传学小组(CCGG)通过使用大肠癌最大的基因型数据集的很大一部分(560,000个标记,1000个病例,1000个对照)来调查遗传标记与结直肠癌之间的关系。然而,对于一个以个人电脑为基础的研究人员(理论运行时间为400天;3.3TB内存和硬盘空间)。CCGG与爱丁堡大学的超级计算中心EPCC合作,对分析代码进行优化和并行化。我们在英国国家超级计算机HECToR的512个处理器核上实现了大约5小时的运行时间。利用EPCC的技术和HPC资源,CCGG在结直肠癌遗传标记分析方面探索了新的领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Search for Gene-Gene Interactions in Colorectal Cancer: Using HPC to Overcome Computational Barriers
UK National Cancer Registration data indicates that some35, 000 people each year are diagnosed with colorectal cancer (cancer of the large bowel and rectum) and 16, 000 die from the disease. The Colon Cancer Genetics Group (CCGG) at the University of Edinburgh investigates the relationship between genetic markers and colorectal cancer by using a significant part (560, 000 markers, 1000 cases, 1000 controls) of the biggest genotypic data set for large bowel cancer. However, the analysis is virtually intractable for a PC-based researcher (theoretical runtime of 400 days; 3.3TB of memory and hard disk space). CCGG collaborated with EPCC, the supercomputing centre of the University of Edinburgh, to optimise and parallelise the analysis code. We achieved a runtime of approximately 5 hours on 512 processor cores on HECToR, the national supercomputer of the UK. The use of EPCC’s skills and HPC resources has enabled CCGG to explore new territory for genetic marker analysis in colorectal cancer.
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