在高性能计算环境中的Omics分析和质量控制管道
Darrell O Ricke1, Derek Ng1, Adam Michaleas1
1Massachusetts Institute of Technology Lincoln Laboratory, Lexington, Massachusetts, USA.
Omics : a journal of integrative biology
|November 9, 2023
概括
新的质量控制 (QC) 管道确保可靠的数据分析. 这些便携式工具可以识别低质量的数据集,并指导表观基因组和转录组研究的实验改进.
科学领域:
- 多主题数据分析数据分析.
- 生物信息学发展管道的发展.
- 生命科学中的质量控制
背景情况:
- 数据质量至关重要,但在欧米学研究中经常被忽视,特别是影响表观基因组和转录基因组的暴露.
- 便携式质量控制 (QC) 管道对于在各种各样的omics数据集中进行一致的分析至关重要.
- 现有的方法可能缺乏标准化,用于在多个omics试验中进行全面的QC.
研究的目的:
- 开发和巩固可移植的质量保证 (QA) 度量和管道,用于12种不同的OMIC分析.
- 建立一个统一的框架来评估和确保omics数据的质量.
- 在涉及化学物质和病原体暴露的研究中解决对标准化质量控制的需求.
主要方法:
- 开发了12个omics测试的便携式质量保证指标和可接受性标准.
- 使用Singularity创建集装箱化QC管道,以实现可移植性和可扩展性.
- 对来自DARPA ECHO计划的人类数据的评估管道性能.
主要成果:
- 成功实施了12个分析质量控制管道,利用标准生物信息学工具.
- 证明了早期识别低质量的数据集和缺乏序列阅读的数据集.
- 突出了需要根据QC管道输出进行改进的实验协议.
结论:
- 开发的omics数据分析和QC管道提高了数据可靠性,并促进了实验优化.
- 这些开源资源为omics和生命科学社区提供了可扩展和可移植的解决方案.
- 标准化QC对于在暴露研究中对表观基因组和转录基因组数据进行可靠的解释至关重要.
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