A PostgreSQL Tripal solution for large-scale genotypic and phenotypic data

Abstract

Abstract Researchers are seeking cost-effective solutions for management and analysis of large-scale genotypic and phenotypic data. Open-source software is uniquely positioned to fill this need through user-focused, crowd-sourced development. Tripal, an open-source toolkit for developing biological data web portals, uses the GMOD Chado database schema to achieve flexible, ontology-driven storage in PostgreSQL. Tripal also aids research-focused web portals in providing data according to findable, accessible, interoperable, reusable (FAIR) principles. We describe here a fully relational PostgreSQL solution to handle large-scale genotypic and phenotypic data that is implemented as a collection of freely available, open-source modules. These Tripal extension modules provide a holistic approach for importing, storage, display and analysis within a relational database schema. Furthermore, they embody the Tripal approach to FAIR data by providing multiple search tools and ensuring metadata is fully described and interoperable. Our solution focuses on data integrity, as well as optimizing performance to provide a fully functional system that is currently being used in the production of Tripal portals for crop species. We fully describe the implementation of our solution and discuss why a PostgreSQL-powered web portal provides an efficient environment for researcher-driven genotypic and phenotypic data analysis.