Purdue research team using community clusters to track COVID-19 variants and malaria
A Purdue professor leading genomic analysis of the novel coronavirus in a university setting is using Research Computing supercomputers in her work, which is critical to tracking variant spread and staying one step ahead of the virus.
Giovanna Carpi, assistant professor of biological sciences and a member of Purdue’s Institute of Inflammation, Immunology and Infectious Disease, uses the Bell cluster to assemble the virus genome in samples taken from individuals with COVID-19 infections. The virus genome can then be used to identify a constellation of mutations that characterize variants of concern.
Ultimately, the detailed COVID-19 genomic analysis from this study “will help us better understand viral spread in congregate settings and the younger population and how we can help mitigate it in the future,” said Carpi, who plans to publish a in-depth study of COVID-19 transmission dynamics in a university setting.
Lev Gorenstein, a senior computational scientist for Research Computing, has helped Carpi’s lab get up and running on the community clusters.
“Lev has been key to making sure we have the software we need, and that the software is updated to the latest release, which is critical to assure accurate COVID-19 variant assignment,” says Carpi.
Carpi works closely with Purdue’s Animal Disease Diagnostic Laboratory, the Protect Purdue Health Center, and the Indiana State Department of Health, which has sent samples directly to her for genome sequencing instead of to the CDC, since her lab (https://www.giovannacarpi.org) can turn results around faster.
Of course the novel coronavirus is not the only pathogen that causes serious disease. In addition to working on COVID-19 genomic surveillance, Carpi focuses on studying malaria parasites in Southern Africa, where malaria is endemic and primarily affects children.
In an ongoing project using the GPU-based Gilbreth community cluster, Carpi is testing and benchmarking Nvidia’s Parabricks GPU-accelerated genomic analysis software as applied to malaria genomes for variant identification, which are then used to understand malaria transmission patterns and track the emergence and spread of antimalaria drug resistance. Gorenstein is assisting Carpi’s lab on this project as well.
“We are trying to develop rapid genomic sequencing and informatic technologies that can be deployed for tracking malaria parasites in resource-constrained malaria endemic settings,” says Carpi.
To learn more about Purdue’s Community Cluster Program, contact Preston Smith, executive director of ITaP Research Computing, firstname.lastname@example.org or 49-49729.