Genomics, DNAnexus Collaborate
News Apr 13, 2016
Genomics plc has announced that it has entered into a research collaboration with DNAnexus. The companies will work together to improve researchers’ ability to analyse population-scale sequencing data. With DNA sequencing costs continuing to fall, sequencing projects involving tens or hundreds of thousands of people are becoming increasingly common.
Such projects include Genomics England’s 100,000 Genomes Project, and the Regeneron Genetics Center and Geisinger Health DiscovEHR collaboration, which is the largest private sector sequencing effort to-date, with the goal of sequencing exomes of 250,000 individuals.
At present, there is a variety of informatics challenges facing such projects – from optimizing and improving existing analytical workflows, to large-scale statistical analysis of cohort data, where linking genome sequencing to parameters of health and disease can be limited by differences in the way samples are sequenced and analysed.
Genomics plc and DNAnexus are addressing these limitations by developing solutions to enable accurate and powerful population-scale data analysis algorithms. Both Genomics plc and DNAnexus are working with the Regeneron Genetics Center, and Genomics plc is a Platform Partner of Genomics England.
John Colenutt, CEO, Genomics plc, said: “Combined analysis of these huge data sets will enable researchers to extract much more information from large scale studies. The longer term goal here is to unlock the potential for researchers to learn more about human biology, in turn leading to better diagnoses and more targeted therapies for patients, and we’re pleased to be working with the DNAnexus team towards this goal.”
Richard Daly, CEO, DNAnexus, said: “The DNAnexus Platform has become the leading solution for analysis providers who are seeking a secure, compliant, and scalable environment, on which they can deploy and extend the reach of their product offerings. We believe that working collaboratively with Genomics plc on cutting-edge population-scale data analysis algorithms will help make the promise of population-scale sequencing analysis a reality.”