IBM Research, Australia, 204 Lygon Street, Carlton, Victoria 3053, Australia.
Department of Biochemistry and Molecular Biology and Bio21 MolecularScience and Biotechnology Institute, The University of Melbourne, Parkville VIC 3010, Victoria, Australia.
Health Inf Sci Syst. 2015 Feb 24;3(Suppl 1 HISA Big Data in Biomedicine and Healthcare 2013 Con):S7. doi: 10.1186/2047-2501-3-S1-S7. eCollection 2015.
Even with the advent of next-generation sequencing (NGS) technologies which have revolutionised the field of bacterial genomics in recent years, a major barrier still exists to the implementation of NGS for routine microbiological use (in public health and clinical microbiology laboratories). Such routine use would make a big difference to investigations of pathogen transmission and prevention/control of (sometimes lethal) infections. The inherent complexity and high frequency of data analyses on very large sets of bacterial DNA sequence data, the ability to ensure data provenance and automatically track and log all analyses for audit purposes, the need for quick and accurate results, together with an essential user-friendly interface for regular non-technical laboratory staff, are all critical requirements for routine use in a public health setting. There are currently no systems to answer positively to all these requirements, in an integrated manner. In this paper, we describe a system for sequence analysis and interpretation that is highly automated and tackles the issues raised earlier, and that is designed for use in diagnostic laboratories by healthcare workers with no specialist bioinformatics knowledge.
即使在近年来革命性地改变了细菌基因组学领域的下一代测序 (NGS) 技术出现之后,将 NGS 用于常规微生物学用途(在公共卫生和临床微生物学实验室中)仍然存在一个主要障碍。这种常规使用将对病原体传播的调查和(有时是致命的)感染的预防/控制产生重大影响。对非常大数据集的细菌 DNA 序列数据进行内在复杂和高频的数据分析、确保数据来源并自动跟踪和记录所有分析以便审核、快速准确的结果以及常规非技术实验室人员的基本用户友好界面,这些都是在公共卫生环境中常规使用的关键要求。目前,没有任何系统能够以集成的方式积极应对所有这些要求。在本文中,我们描述了一个高度自动化的序列分析和解释系统,该系统解决了前面提到的问题,专为没有专业生物信息学知识的医疗保健工作者在诊断实验室中使用而设计。