Analysis and visualization of Arabidopsis thaliana GWAS using web 2.0 technologies

Yu S. Huang, Matthew Horton, Bjarni J. Vilhjálmsson, Ümit Seren, Dazhe Meng, Christopher Meyer, Muhammad Ali Amer, Justin O. Borevitz, Joy Bergelson, Magnus Nordborg

Research output: Contribution to journalArticlepeer-review


With large-scale genomic data becoming the norm in biological studies, the storing, integrating, viewing and searching of such data have become a major challenge. In this article, we describe the development of an Arabidopsis thaliana database that hosts the geographic information and genetic polymorphism data for over 6000 accessions and genome-wide association study (GWAS) results for 107 phenotypes representing the largest collection of Arabidopsis polymorphism data and GWAS results to date. Taking advantage of a series of the latest web 2.0 technologies, such as Ajax (Asynchronous JavaScript and XML), GWT (Google-Web-Toolkit), MVC (Model-View-Controller) web framework and Object Relationship Mapper, we have created a web-based application (web app) for the database, that offers an integrated and dynamic view of geographic information, genetic polymorphism and GWAS results. Essential search functionalities are incorporated into the web app to aid reverse genetics research. The database and its web app have proven to be a valuable resource to the Arabidopsis community. The whole framework serves as an example of how biological data, especially GWAS, can be presented and accessed through the web. In the end, we illustrate the potential to gain new insights through the web app by two examples, showcasing how it can be used to facilitate forward and reverse genetics research.

Original languageEnglish (US)
Article numberbar014
StatePublished - 2011

ASJC Scopus subject areas

  • Information Systems
  • General Biochemistry, Genetics and Molecular Biology
  • General Agricultural and Biological Sciences


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