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

Lacey-Anne Sanderson1, Carolyn T Caron1, Reynold L Tan1

  • 1Department of Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon SK S7N 5A8, Canada.

Database : the Journal of Biological Databases and Curation
|August 14, 2021
PubMed
Summary

Open-source Tripal software offers a cost-effective solution for managing large-scale genotypic and phenotypic data. This toolkit enables efficient data analysis and sharing, adhering to FAIR data principles.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Managing and analyzing large-scale genotypic and phenotypic data presents significant cost and efficiency challenges.
  • Open-source software development offers a promising avenue for creating user-focused, crowd-sourced solutions.

Purpose of the Study:

  • To present a cost-effective, open-source solution for the management and analysis of large-scale genotypic and phenotypic data.
  • To detail a PostgreSQL-based web portal implementation using the Tripal toolkit that adheres to FAIR data principles.

Main Methods:

  • Utilized the Tripal open-source toolkit and the GMOD Chado database schema for flexible, ontology-driven data storage in PostgreSQL.
  • Developed a collection of open-source modules for importing, storing, displaying, and analyzing genotypic and phenotypic data within a relational database.
  • Implemented features to ensure data integrity, optimize performance, and provide multiple search tools for interoperable metadata.

Main Results:

  • A fully relational PostgreSQL solution was implemented for handling large-scale genotypic and phenotypic data.
  • The Tripal extension modules facilitate a holistic approach to data management, aligning with Findable, Accessible, Interoperable, and Reusable (FAIR) data principles.
  • The system is currently in production for crop species Tripal portals, demonstrating its functionality and efficiency.

Conclusions:

  • A PostgreSQL-powered web portal, built with Tripal modules, provides an efficient and cost-effective environment for researcher-driven genotypic and phenotypic data analysis.
  • The open-source approach fosters crowd-sourced development, enhancing the usability and accessibility of biological data management tools.
  • The implemented solution successfully addresses the need for robust, FAIR-compliant data management in genomics research.