Format

Send to

Choose Destination
J Clin Microbiol. 2018 Oct 25;56(11). pii: e00480-18. doi: 10.1128/JCM.00480-18. Print 2018 Nov.

Real-Time Analysis and Visualization of Pathogen Sequence Data.

Author information

1
Biozentrum, University of Basel, Basel, Switzerland richard.neher@unibas.ch.
2
SIB Swiss Institute of Bioinformatics, Basel, Switzerland.
3
Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.

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 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.

KEYWORDS:

bioinformatics; molecular epidemiology; phylogenetic analysis

PMID:
30135232
DOI:
10.1128/JCM.00480-18

Supplemental Content

Full text links

Icon for HighWire
Loading ...
Support Center