Skip to main content
ARS Home » Research » Publications at this Location » Publication #234771

Title: The PRRS Host Genomic Consortium (PHGC) Database: Management of large data sets.

Author
item FRITZ, ERIC - IOWA STATE UNIV
item Lunney, Joan
item HU, ZHI-LIANG - IOWA STATE UNIV
item REECY, JAMES - IOWA STATE UNIV

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 8/30/2008
Publication Date: 12/4/2008
Citation: Fritz, E., Lunney, J.K., Hu, Z., Reecy, J. 2008. The PRRS Host Genomic Consortium (PHGC) Database: Management of large data sets. p. 324.

Interpretive Summary:

Technical Abstract: In any consortium project where large amounts of phenotypic and genotypic data are collected across several research labs, issues arise with maintenance and analysis of datasets. The PRRS Host Genomic Consortium (PHGC) Database was developed to meet this need for the PRRS research community. The schema for the database was originally designed based on data sets generated from the PRRS virus “Big Pig” project. This included data on pig, sex, birth date and infection details, PRRS viral levels in serum over time and tissue levels at kill, anti-PRRSV antibody (ELISA and neutralizing antibody) responses, serum cytokine levels and tissue gene expression results, and Swine Leukocyte Antigen (SLA) alleles. This internet accessible relational database was designed to allow for the addition of new data types as they are generated over the course of the project. This flexibility will allow us to house and manage all of the PHGC project data, to build quality control (QC) filters and design improved procedures for data flow, and allow real-time data updates and sharing among users from geographically different locations. Furthermore, use of a centralized database will allow us to control external access to the data, e.g., data could be made available to the general public, restricted to only consortium members, or even to just a few members. Overall, the PHGC database will allow us to properly manage large datasets and affords new possibilities for exploration of the resultant data. Support: NPB funds.