The Integrated Rapid Infectious Disease Analysis (IRIDA) Platform
Authors: Matthews Thomas C , Bristow Franklin R , Griffiths Emma J , Petkau Aaron , Adam Josh , Dooley Damion , Kruczkiewicz Peter , Curatcha John , Cabral Jennifer , Fornika Dan , Winsor Geoffrey L. , Courtot Melanie , Bertelli Claire , Roudgar Ataollah , Feijao Pedro , Mabon Philip , Enns Eric , Thiessen Joel , Keddy Alexander , Isaac-Renton Judith , Gardy Jennifer L. , Tang Patrick , João A Carriço The IRIDA Consortium , Chindelevitch Leonid , Chauve Cedric , Graham Morag R , McArthur Andrew G , Taboada Eduardo N , Beiko Robert G , Brinkman Fiona SL , Hsiao William WL , Domselaar Gary Van 
Published: July 2018

Whole genome sequencing (WGS) is a powerful tool for public health infectious disease investigations owing to its higher resolution, greater efficiency, and cost-effectiveness over traditional genotyping methods. Implementation of WGS in routine public health microbiology laboratories is impeded by a lack of user-friendly automated and semi-automated pipelines, restrictive jurisdictional data sharing policies, and the proliferation of non-interoperable analytical and reporting systems. To address these issues, we developed the Integrated Rapid Infectious Disease Analysis (IRIDA) platform (irida.ca), a user-friendly, decentralized, open-source bioinformatics and analytical web platform to support real-time infectious disease outbreak investigations using WGS data. Instances can be independently installed on local high-performance computing infrastructure, enabling private and secure data management and analyses according to organizational policies and governance. IRIDA’s data management capabilities enable secure upload, storage and sharing of all WGS data and metadata. The core platform currently includes pipelines for quality control, assembly, annotation, variant detection, phylogenetic analysis, in silico serotyping, multi-locus sequence typing, and genome distance calculation. Analysis pipeline results can be visualized within the platform through dynamic line lists and integrated phylogenomic clustering for research and discovery, and for enhancing decision-making support and hypothesis generation in epidemiological investigations. Communication and data exchange between instances are provided through customizable access controls. IRIDA complements centralized systems, empowering local analytics and visualizations for genomics-based microbial pathogen investigations. IRIDA is currently transforming the Canadian public health ecosystem and is freely available at https://github.com/phac-nml/irida and www.irida.ca.

Impact Statement

Whole genome sequencing (WGS) is revolutionizing infectious disease analysis and surveillance due to its cost effectiveness, utility, and improved analytical power. To date, no “one-size-fits-all” genomics platform has been universally adopted, owing to differences in national (and regional) health information systems, data sharing policies, computational infrastructures, lack of interoperability and prohibitive costs. The Integrated Rapid Infectious Disease Analysis (IRIDA) platform is a user-friendly, decentralized, open-source bioinformatics and analytical web platform developed to support real-time infectious disease outbreak investigations using WGS data. IRIDA empowers public health, regulatory and clinical microbiology laboratory personnel to better incorporate WGS technology into routine operations by shielding them from the computational and analytical complexities of big data genomics. IRIDA is now routinely used as part of a validated suite of tools to support outbreak investigations in Canada. While IRIDA was designed to serve the needs of the Canadian public health system, it is generally applicable to any public health and multi-jurisdictional environment. IRIDA enables localized analyses but provides mechanisms and standard outputs to enable data sharing. This approach can help overcome pervasive challenges in real-time global infectious disease surveillance, investigation and control, resulting in faster responses, and ultimately, better public health outcomes.

DATA SUMMARY

Data used to generate some of the figures in this manuscript can be found in the NCBI BioProject PRJNA305824.