Data integration and analysis for mapping malaria parasite traits

NIH RePORTER · NIH · P01 · $188,187 · view on reporter.nih.gov ↗

Abstract

ABSTRACT The ability to conduct targeted genetic crosses in malaria provides exciting opportunities to uncover genetic mechanisms linked to drug resistance. Core B will provide a centralized resource for all project data, standardized bioinformatics analysis, the integrated, network-based analysis required by RP02 and RP03. All of these data and results will then be deposited in relevant public resources. Extensive –omics data will be collected for each progeny clone (i.e., transcripts, proteins and metabolites) and deposited in public archives by Core C. Because such data from the large numbers of unique recombinant progeny provided by Core A/RP01 are more powerful when integrated, Core B will maintain the required computational infrastructure to standardize project metadata and link genotypes to collected phenotypes. In tandem with RP02, Core B serves as the focal point of all project data. Because our efforts will also generate specialized metadata for which no standard archives exist, we will work closely with EuPathDB to ensure timely and relevant community access of all Project data. Providing standard analysis and significant hardware resources will also open up new avenues of integrated data analysis within the Project, which in turn will be shared via EuPathDB. Further, these significant, metadata- labeled collections of data will provide an extremely rich resource for bioinformaticians and computational biologists. Although publically available datasets of this scope and size are only available for cancer biology, they have been invaluable in the development of computational methods, e.g., predicting drug combination efficiency. We imagine our resource would be just as popular and recruit many participants to improve prediction of drug responses and other biological traits in malaria parasites. In addition to a letter of support from EupathDB on community access, we also include a letter from African researchers who are already highly interested in this data resource.

Key facts

NIH application ID
10216644
Project number
5P01AI127338-05
Recipient
UNIVERSITY OF NOTRE DAME
Principal Investigator
Scott Emrich
Activity code
P01
Funding institute
NIH
Fiscal year
2021
Award amount
$188,187
Award type
5
Project period
2017-08-01 → 2024-04-30