Presenter of 1 Presentation
O021 - RAPID, INTERACTIVE AND SECURE ANALYSIS OF PNEUMOCOCCAL SEQUENCING DATA FOR ON-SITE EPIDEMIOLOGY (ID 303)
Abstract
Background
Genomic surveillance of pneumococci promises to revolutionize how we trace the global spread of strains, detect resistance, and make decisions on how to control disease. However, complex and cumbersome methods, barriers to data integration, and reproducibility issues with currently used genotyping schemes have prevented the translation of technological innovation into the clinic.
Methods
Our core method, PopPUNK, uses a machine learning approach to produce a stable, consistent genotyping scheme reflecting pneumococcal population biology. We have extended this software to use customised genome sketching techniques to enhance its flexibility, scalability, and portability. We also provide a machine-learning based approach for determining susceptibility to antimicrobials.
Results
We have defined the structure of the pneumococcal species by applying our method to over 50,000 globally sampled genomes. Users can rapidly integrate their own sequences into the context of this global population, directly from the browser, and visualise the results without the need for bioinformatics expertise. Phylogenetic analysis of sub-populations, for example to determine outbreak characteristics, has also been optimised and automated. Unlike some other platforms, users will not be required to give away any rights to their data, and sequence data never leaves the local machine.
Conclusions
Our software suite empowers local epidemiologists to perform analysis onsite, regardless of prior expertise, available computational resources, or location.