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.

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 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Copyright Owner

The Authors

Language

en

File Format

application/pdf

Published Version

Share

COinS