Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan.
Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.
Bioinformatics. 2018 Sep 1;34(17):3047-3049. doi: 10.1093/bioinformatics/bty219.
Exhaustive detection of multi-loci markers from genome-wide association study datasets is a computationally challenging problem. This paper presents a massively parallel algorithm for finding all significant combinations of alleles and introduces a software tool termed MP-LAMP that can be easily deployed in a cloud platform, such as Amazon Web Service, as well as in an in-house computer cluster. Multi-loci marker detection is an unbalanced tree search problem that cannot be parallelized by simple tree-splitting using generic parallel programming frameworks, such as Map-Reduce. We employ work stealing and periodic reduce-broadcast to decrease the running time almost linearly to the number of cores.
MP-LAMP is available at https://github.com/tsudalab/mp-lamp.
Supplementary data are available at Bioinformatics online.
从全基因组关联研究数据集中穷尽地检测多基因座标记是一个计算上具有挑战性的问题。本文提出了一种用于寻找所有等位基因显著组合的大规模并行算法，并介绍了一个名为 MP-LAMP 的软件工具，该工具可以轻松部署在云平台（如亚马逊网络服务）以及内部计算机集群中。多基因座标记检测是一个不平衡的树搜索问题，不能通过使用通用并行编程框架（如 Map-Reduce）简单地通过树分割进行并行化。我们采用工作窃取和周期性的减少广播来将运行时间几乎线性地减少到核心数量。
MP-LAMP 可在 https://github.com/tsudalab/mp-lamp 上获得。
补充数据可在生物信息学在线获得。
