Introducing field-programmable gate arrays in genotype phasing and imputation.

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY

Bioinformatics advances Pub Date : 2024-07-30 eCollection Date: 2024-01-01 DOI:10.1093/bioadv/vbae114

Lars Wienbrandt, David Ellinghaus

引用次数: 0

Abstract

Summary: We recently developed EagleImp, a free software that combines genotype phasing and imputation in a single tool. By introducing algorithmic and technical improvements we accelerated the classical two-step approach using Eagle2 and PBWT. Here, we demonstrate how to use field-programmable gate arrays (FPGAs) to accelerate EagleImp even further by a factor of up to 93% without loss of phasing and imputation quality. Due to the speed advantage over a not accelerated processor-based implementation, the FPGA extension of EagleImp allows the user to choose a more resource-intensive parameter setting in exchange for computation time to further improve phasing and imputation quality.

Availability and implementation: EagleImp and its FPGA extension are freely available at https://github.com/ikmb/eagleimp and https://github.com/ikmb/eagleimp-fpga.

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将现场可编程门阵列引入基因型分期和估算。

摘要：我们最近开发了一款免费软件 EagleImp，它将基因型分期和归因结合在一个工具中。通过引入算法和技术改进，我们加速了使用 Eagle2 和 PBWT 的经典两步法。在这里，我们展示了如何使用现场可编程门阵列（FPGA）将 EagleImp 的速度进一步提高 93%，而不会降低分期和归因的质量。由于与未加速的基于处理器的实现相比具有速度优势，EagleImp 的 FPGA 扩展允许用户选择更耗费资源的参数设置，以换取计算时间，从而进一步提高相位和估算质量：EagleImp 及其 FPGA 扩展可在 https://github.com/ikmb/eagleimp 和 https://github.com/ikmb/eagleimp-fpga 免费获取。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Bioinformatics advances

CiteScore

1.60

自引率

0.00%

发文量