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Table 3 Whole-genome sequencing in outbreak investigations: opportunities and challenges

From: Genomics and outbreak investigation: from sequence to consequence

Feature Opportunities Challenges
Sequence generation Provision of data on a timescale that allows clinical interventions
Costs now comparable to those of other clinically relevant expenditure (such as of antibiotic treatment or bed occupancy)
Use now comparable to that of other automated laboratory systems
Delivers far richer data than any previous method
Potential for open-ended one-size-fits-all culture-independent workflow
Chasing a moving target: difficult to devise stable and agreed standard operating procedures in the face of relentless technical innovation
Proof needed that WGS cost-effective across a range of clinical applications
Difficulties in predicting phenotype from genotype
Still sufficiently technically demanding to require input of skilled staff
Resistance to adoption of potentially disruptive technology
Data handling Provides portable, digital, library-based approach Large datasets require significant hardware for storage and analysis
Need for standardized, robust, user-friendly analysis pipelines
Issues over data storage, ownership and presentation need to be resolved
Integration with healthcare informatics systems to allow easy communication with clinicians
Epidemiological analysis WGS provides highest possible resolution
Potential to link pathogen discovery, biology and evolution with phylogeny and epidemiology to facilitate iterative hypothesis generation, testing and refinement
Need to move beyond SNP typing of draft genomes of colony-purified isolates to embrace full range of genome variation, including within-patient variation
Better integration with conventional epidemiology required to place data in context and evaluate hypothesized routes of transmissions
Acquiring clinical metadata often remains a bottleneck