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

**Authors:** Lars Wienbrandt, David Ellinghaus

PMC · DOI: 10.1093/bioadv/vbae114 · 2024-07-30

## TL;DR

This paper introduces an FPGA-accelerated version of EagleImp, a tool for genotype phasing and imputation, significantly speeding up the process without sacrificing quality.

## Contribution

The novel use of FPGAs to accelerate genotype phasing and imputation, achieving up to 93% faster performance.

## Key findings

- FPGA acceleration improves EagleImp's performance by up to 93%.
- Phasing and imputation quality remains unchanged with FPGA acceleration.
- Users can now trade computation time for better quality using more resource-intensive settings.

## Abstract

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.

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

## Full-text entities

- **Diseases:** COVID-19 (MESH:D000086382), c-d (MESH:C538319), Chronic Inflammation (MESH:D007249)
- **Chemicals:** DRAM (-)

## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11333566/full.md

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Source: https://tomesphere.com/paper/PMC11333566