在资源有限的设备上进行高效的实时选择性基因组测序
Po Jui Shih1, Hassaan Saadat2, Sri Parameswaran3
1School of Computer Science and Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.
GigaScience
|July 3, 2023
概括
硬件加速读取 (HARU) 能够在资源有限的设备上实现高效的纳米孔选择性测序. 这种方法显著加快了实时基因组分析的速度,使得快速遗传测试更容易获得和节能.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 第三代纳米孔测序器能够进行选择性测序 (Read Until) 以实时分析.
- 这项技术对于快速,低成本的基因测试等应用至关重要.
- 当前后续动态时间曲 (sDTW) 方法是计算密集的,阻碍便携式测序器的实时分析.
研究的目的:
- 开发一种资源高效的方法来加速纳米孔选择性测序的sDTW算法.
- 在便携式和资源有限的设备上实现实时基因组分析.
主要方法:
- 引入了硬件加速读取 (HARU),一种硬件-软件代码设计方法.
- 使用了一个异质的多处理器芯片上的系统 (SoC) 与芯片上的现场可编程网关阵列 (FPGA).
- 加快sDTW算法进行实时读取分析.
主要成果:
- 与36核服务器上的优化软件相比,HARU实现了2.5倍的速度,使用Xilinx FPGA与4核ARM处理器.
- 与未经优化软件相比,显示了85倍的加快速度.
- 与基于服务器的执行相比,能源消耗减少了两个数量级.
结论:
- 在资源有限的设备上,HARU成功实现了纳米孔选择性测序.
- 这种方法突出了硬件和软件优化的潜力,用于便携式基因组分析.
- 哈鲁的开源代码可供进一步开发和应用.
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