Analysis and visualization of Arabidopsis thaliana GWAS using web 2.0 technologies

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 polymo...

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Main Authors:	Huang, Yu S., Horton, Matthew, Vilhjálmsson, Bjarni J., Seren, Ümit, Meng, Dazhe, Meyer, Christopher, Ali Amer, Muhammad, Borevitz, Justin O., Bergelson, Joy, Nordborg, Magnus
Format:	Online
Language:	English
Published:	Oxford University Press 2011
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3243604/

id	pubmed-3243604
recordtype	oai_dc
spelling	pubmed-32436042011-12-20 Analysis and visualization of Arabidopsis thaliana GWAS using web 2.0 technologies Huang, Yu S. Horton, Matthew Vilhjálmsson, Bjarni J. Seren, Ümit Meng, Dazhe Meyer, Christopher Ali Amer, Muhammad Borevitz, Justin O. Bergelson, Joy Nordborg, Magnus Database Tool 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. Database URL: http://arabidopsis.usc.edu/ Oxford University Press 2011-05-23 /pmc/articles/PMC3243604/ /pubmed/21609965 http://dx.doi.org/10.1093/database/bar014 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 This is Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Huang, Yu S. Horton, Matthew Vilhjálmsson, Bjarni J. Seren, Ümit Meng, Dazhe Meyer, Christopher Ali Amer, Muhammad Borevitz, Justin O. Bergelson, Joy Nordborg, Magnus
spellingShingle	Huang, Yu S. Horton, Matthew Vilhjálmsson, Bjarni J. Seren, Ümit Meng, Dazhe Meyer, Christopher Ali Amer, Muhammad Borevitz, Justin O. Bergelson, Joy Nordborg, Magnus Analysis and visualization of Arabidopsis thaliana GWAS using web 2.0 technologies
author_facet	Huang, Yu S. Horton, Matthew Vilhjálmsson, Bjarni J. Seren, Ümit Meng, Dazhe Meyer, Christopher Ali Amer, Muhammad Borevitz, Justin O. Bergelson, Joy Nordborg, Magnus
author_sort	Huang, Yu S.
title	Analysis and visualization of Arabidopsis thaliana GWAS using web 2.0 technologies
title_short	Analysis and visualization of Arabidopsis thaliana GWAS using web 2.0 technologies
title_full	Analysis and visualization of Arabidopsis thaliana GWAS using web 2.0 technologies
title_fullStr	Analysis and visualization of Arabidopsis thaliana GWAS using web 2.0 technologies
title_full_unstemmed	Analysis and visualization of Arabidopsis thaliana GWAS using web 2.0 technologies
title_sort	analysis and visualization of arabidopsis thaliana gwas using web 2.0 technologies
description	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. Database URL: http://arabidopsis.usc.edu/
publisher	Oxford University Press
publishDate	2011
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3243604/
_version_	1611495937399586816

Analysis and visualization of Arabidopsis thaliana GWAS using web 2.0 technologies

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