SimReadUntil用于对ONT设备上的选择性测序算法进行基准测试
Maximilian Mordig1,2, Gunnar Rätsch1,3,4,5, André Kahles1,3,4
1Biomedical Informatics Group, Department of Computer Science, ETH Zurich, Zürich, 8092, Switzerland.
Bioinformatics (Oxford, England)
|April 11, 2024
概括
SimReadUntil模拟了牛津纳米孔技术 (ONT) 选择性测序,使高效的算法开发成为可能. 这个工具提供了basecalled读取,减少了计算负载并消除了对GPU的需求,加速了选择性测序决策算法 (SSDA) 的优化.
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.
- 计算生物学 计算生物学
背景情况:
- 牛津纳米孔技术 (ONT) ReadUntil API为基因组丰富或耗尽提供了选择性测序.
- 优化选择性测序决策算法 (SSDA) 对性能至关重要,但由于昂贵且耗时的真实测序运行而受到阻碍.
- 现有的模拟工具是内存密集型,需要大数据文件,并专注于原始信号数据,使SSDA开发复杂化.
研究的目的:
- 开发一个新的ONT设备模拟器,SimReadUntil,支持ReadUntil API,以进行高效的SSDA评估.
- 通过使用basecalled读取而不是原始信号来减少计算负载的模拟环境.
- 为了方便SSDA工具如ReadFish和ReadBouncer的参数调整,而不需要GPU加速的基础调用.
主要方法:
- SimReadUntil通过实时播放完整的读数来模拟ONT序列,包括通道噪声和阻塞.
- 模拟器允许读取拒绝和终止数据接收,模仿ReadUntil API功能.
- 一个gRPC接口能够在各种编程语言之间进行标准化交互,并提供了从序列总结文件中提取模拟参数的方法.
主要成果:
- SimReadUntil成功模拟了ONT选择性测序,提供了直接SSDA评估的基础调用读取.
- 模拟器减少了计算要求,通过消除对GPU的需求,使SSDA开发更容易获得.
- 该工具被调整为复制使用ReadFish的丰富实验,展示其实际应用.
结论:
- SimReadUntil提供了一个有价值,高效和可访问的平台,用于开发和优化ONT设备上的选择性测序策略.
- 该模拟器简化了研究人员的工作流程,加速了生物信息学工具的进步,用于有针对性的测序应用.
- 在GitHub上开源的可用性促进了协作开发和科学界更广泛的采用.
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