Real-time analysis and visualization of pathogen sequence data

Abstract

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 toreconstruct the evolution of pathogens, to anticipate future spread, and to target interventions. In clinical settings, whole-genome sequencing can identify pathogens atthe strain level, can be used to predict phenotypes such as drug resistance and virulence, and can inform treatment by linking closely related cases. While sequencinghas 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 dauntingtask that requires flexible bioinformatic workflows and dissemination platforms.Here, we review recent developments in real-time analyses of pathogen sequencedata, with a particular focus on the visualization and integration of sequence andphenotype data.