Reference-Based Haplotype Phasing with FPGAs
Reference-Based Haplotype Phasing with FPGAs
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DOI：
10.1007/978-3-030-50420-5_36
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发表时间：
2020-05-22
期刊：
影响因子：
--
通讯作者：
Ellinghaus D
中科院分区：
文献类型：
--
作者：
Wienbrandt L;Kässens JC;Ellinghaus D
单个样品的单体型定相通常作为基因型插补之前的前体步骤进行，以降低插补步骤的运行时复杂性并提高插补准确性。阶段化过程是耗时的，并且即使在服务器级计算系统上也通常超过数小时。洛等人最近介绍了一种名为EAGLE 2的快速有效的基于参考的单倍型定相软件，该软件随参考样品和变体的数量线性缩放以定相。我们发现，从EAGLE2阶段化过程的几个步骤中，内部使用的HapHedge数据结构的数据准备已经消耗了一般用例中总运行时间的一半左右。我们通过引入一种新的可重构架构设计来解决这个问题，该设计在Xilinx Kintex UltraScale FPGA上将这部分软件加速高达29倍，与具有两个Intel Xeon CPU的服务器级计算系统相比，整个阶段过程的总加速率几乎为2（根据Amdahl定律的理论极限）。因此，我们使用1000个基因组项目参考面板在我们的系统上将2500个样本中520，000个变异体的全基因组定相的EAGLE2运行时间从68分钟减少到39分钟，同时保持质量。
Haplotype phasing of individual samples is commonly carried out as a precursor step before genotype imputation to reduce the runtime complexity of the imputation step and to improve imputation accuracy. The phasing process is time-consuming and generally exceeds hours even on server-grade computing systems. Loh et al. recently introduced a fast and effective reference-based haplotype phasing software named EAGLE2 which scales linearly with the number of reference samples and variants to phase. We discovered that from the several steps of the EAGLE2 phasing process, data preparation for the internally used HapHedge data structure already consumes about half of the total runtime in general use cases. We addressed this problem by introducing a new design for reconfigurable architectures that accelerates this part of the software by a factor of up to 29 on a Xilinx Kintex UltraScale FPGA, resulting in a total speedup of the complete phasing process of almost 2 (the theoretical limit according to Amdahl’s Law) when compared to a server-grade computing system with two Intel Xeon CPUs. As a result, we reduced the EAGLE2 runtime of genome-wide phasing of 520,000 variants in 2500 samples using the 1000 Genomes Project reference panel from 68 min to 39 min on our system while maintaining quality.
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影响因子：
30.8
作者：
Das, Sayantan;Forer, Lukas;Schoenherr, Sebastian;Sidore, Carlo;Locke, Adam E.;Kwong, Alan;Vrieze, Scott I.;Chew, Emily Y.;Levy, Shawn;McGue, Matt;Schlessinger, David;Stambolian, Dwight;Loh, Po-Ru;Iacono, William G.;Swaroop, Anand;Scott, Laura J.;Cucca, Francesco;Kronenberg, Florian;Boehnke, Michael;Abecasis, Goncalo R.;Fuchsberger, Christian
通讯作者：
Fuchsberger, Christian
影响因子：
30.8
作者：
Loh, Po-Ru;Danecek, Petr;Palamara, Pier Francesco;Fuchsberger, Christian;Reshef, Yakir A.;Finucane, Hilary K.;Schoenherr, Sebastian;Forer, Lukas;McCarthy, Shane;Abecasis, Goncalo R.;Durbin, Richard;Price, Alkes L.
通讯作者：
Price, Alkes L.
DOI：
10.1093/bioinformatics/btu014
发表时间：
2014-05-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Durbin R
通讯作者：
Durbin R
影响因子：
64.8
作者：
1000 Genomes Project Consortium;Auton A;Brooks LD;Durbin RM;Garrison EP;Kang HM;Korbel JO;Marchini JL;McCarthy S;McVean GA;Abecasis GR
通讯作者：
Abecasis GR
影响因子：
9.8
作者：
Wiliams, Amy L.;Patterson, Nick;Reich, David
通讯作者：
Reich, David