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GWASpro: A High-Performance Genome-Wide Association Analysis Server
Bioinformatics
  • Bongsong KIm, Noble Research Institute
  • Xinbin Dai, Noble Research Institute
  • Wenchao Zhang, Noble Research Institute
  • Zhaohong Zhuang, Noble Research Institute
  • Darlene L. Sanchez, Texas A&M AgriLife Research
  • Thomas Lubberstedt, Iowa State University
  • Yun Kang, Noble Research Institute
  • Michael Udvardi, Noble Research Institute
  • William D. Beavis, Iowa State Univeristy
  • Shizhong Xu, University of California, Riverside
  • Patrick X. Zhao, Noble Research Institute
Document Type
Article
Publication Version
Accepted Manuscript
Publication Date
1-1-2018
DOI
10.1093/bioinformatics/bty989
Abstract

We present GWASpro, a high-performance web server for the analyses of large-scale genome-wide association studies (GWAS). GWASpro was developed to provide data analyses for large-scale molecular genetic data, coupled with complex replicated experimental designs such as found in plant science investigations, and to overcome the steep learning curves of existing GWAS software tools. GWASpro supports building complex design matrices, by which complex experimental designs that may include replications, treatments, locations and times, can be accounted for in the linear mixed model (LMM). GWASpro is optimized to handle GWAS data that may consist of up to 10 million markers and 10,000 samples from replicable lines or hybrids. GWASpro provides an interface that significantly reduces the learning curve for new GWAS investigators.

Comments

This is a manuscript of an article published as Kim, Bongsong, Xinbin Dai, Wenchao Zhang, Zhaohong Zhuang, Darlene L. Sanchez, Thomas Lübberstedt, Yun Kang et al. "GWASpro: A High-Performance Genome-Wide Association Analysis Server." Bioinformatics (2018). doi: 10.1093/bioinformatics/bty989.

Creative Commons License
Creative Commons Attribution 4.0 International
Copyright Owner
The Authors
Language
en
File Format
application/pdf
Citation Information
Bongsong KIm, Xinbin Dai, Wenchao Zhang, Zhaohong Zhuang, et al.. "GWASpro: A High-Performance Genome-Wide Association Analysis Server" Bioinformatics (2018)
Available at: http://works.bepress.com/thomas-lubberstedt/92/