科里奥利斯:在轻型移动设备上实现元基因组分类
Andrew J Mikalsen1, Jaroslaw Zola1
1Department of Computer Science and Engineering, University at Buffalo, Buffalo, NY 14260, United States.
Bioinformatics (Oxford, England)
|June 30, 2023
概括
便携式DNA测序需要基于现场的分类. 我们开发了Coriolis,这是一款用于移动设备的元基因组分类器,为实时DNA分析提供高吞吐量和低资源使用.
科学领域:
- 生物信息学是一种生物信息学.
- 基因组学就是基因组学.
- 移动计算 移动计算
背景情况:
- 像牛津纳米孔MiniON这样的便携式DNA测序器可以进行现场测序.
- 在现场DNA分类对于可操作的元基因组分析至关重要.
- 移动部署面临挑战:有限的连接和计算能力.
研究的目的:
- 在移动设备上开发实地元基因组分类策略.
- 为满足在内存受限设备上有效部署DNA数据库的需求.
- 为轻量级移动平台创建一个优化的元基因组分类器.
主要方法:
- 引入了一个具有可管理的抽象的元基因组分类器的编程模型.
- 开发了紧的字符串B树,用于在移动设备上索引大型DNA数据库.
- 将这些解决方案集成到Coriolis中,这是一个移动优化的元基因组分类器.
主要成果:
- 与最先进的解决方案相比,科里奥利斯显示出更高的吞吐量和更低的资源消耗.
- 紧的字符串B树被证明是可行的部署大规模的DNA数据库在内存受限的设备上.
- 实验证实了科里奥利斯在使用便携式超级计算机对实际MINION元基因组读数的有效性.
结论:
- 科里奥利斯可以在移动设备上进行高效的现场元基因组分类.
- 拟议的编程模型和数据结构促进了资源有限的生物信息学.
- 这项工作支持远程现场设置中的实时可操作的元基因组分析.
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