Biozentrum, University of Basel, Basel, Switzerland
SIB Swiss Institute of Bioinformatics, Basel, Switzerland.
J Clin Microbiol. 2018 Oct 25;56(11). doi: 10.1128/JCM.00480-18. Print 2018 Nov.
The rapid development of sequencing technologies has to led to an explosion of pathogen sequence data, which are increasingly collected as part of routine surveillance or clinical diagnostics. In public health, sequence data are used to reconstruct the evolution of pathogens, to anticipate future spread, and to target interventions. In clinical settings, whole-genome sequencing can identify pathogens at the strain level, can be used to predict phenotypes such as drug resistance and virulence, and can inform treatment by linking closely related cases. While sequencing has become cheaper, the analysis of sequence data has become an important bottleneck. Deriving interpretable and actionable results for a large variety of pathogens, each with its own complexity, from continuously updated data is a daunting task that requires flexible bioinformatic workflows and dissemination platforms. Here, we review recent developments in real-time analyses of pathogen sequence data, with a particular focus on the visualization and integration of sequence and phenotype data.
测序技术的快速发展导致了病原体序列数据的爆炸式增长，这些数据越来越多地作为常规监测或临床诊断的一部分被收集。在公共卫生领域，序列数据被用于重建病原体的进化，预测未来的传播，并针对干预措施进行目标定位。在临床环境中，全基因组测序可以在菌株水平上识别病原体，可用于预测耐药性和毒力等表型，并通过将密切相关的病例联系起来指导治疗。虽然测序变得更便宜了，但序列数据的分析已成为一个重要的瓶颈。从不断更新的数据中，为各种具有自身复杂性的病原体提取可解释和可操作的结果，是一项艰巨的任务，需要灵活的生物信息学工作流程和传播平台。在这里，我们综述了病原体序列数据实时分析的最新进展，特别关注序列和表型数据的可视化和整合。
