Campus Units
Agronomy
Document Type
Article
Publication Version
Accepted Manuscript
Publication Date
2018
Journal or Book Title
Bioinformatics
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.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright Owner
The Authors
Copyright Date
2018
Language
en
File Format
application/pdf
Recommended Citation
KIm, Bongsong; Dai, Xinbin; Zhang, Wenchao; Zhuang, Zhaohong; Sanchez, Darlene L.; Lubberstedt, Thomas; Kang, Yun; Udvardi, Michael; Beavis, William D.; Xu, Shizhong; and Zhao, Patrick X., "GWASpro: A High-Performance Genome-Wide Association Analysis Server" (2018). Agronomy Publications. 553.
https://lib.dr.iastate.edu/agron_pubs/553
Included in
Agriculture Commons, Bioinformatics Commons, Molecular Genetics Commons, Plant Breeding and Genetics Commons
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.