Author

Hui Tang

Shandong Agricultural UniversityORCID 0000-0002-4232-4607Unclaimed ORCID profile · follow to get notified of new preprints

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Hui Tang4 papers · Medical University of South Carolina

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:GWAS / association mapping· 2 Approach:mixed model· 2 Organism:yeast· 2 Research Focus:benchmarking· 1 Assay:GWAS summary statistics· 1 Organism:human· 1 Approach:statistical model· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Chao NingiD· 2 shared Dan WangiD· 2 shared Shizhong XuiD· 2 shared Jianfeng LiuiD· 1 shared Jun TengiD· 1 shared Pengju ZhaoiD· 1 shared Qin ZhangiD· 1 shared Qin ZhangiD· 1 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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2 shared papersBioinformatics

Chao NingORCID

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2 papers

Recent·Most cited

An Improved Linear Mixed Model for Multivariate Genome-Wide Association Studies

Dan Wang, Jun Teng, Pengju Zhao, Xinhao Zhang, Hui Tang, Xinzhong Fan, Shizhong Xu, Qin Zhang, Chao Ning

This paper introduces an improved linear mixed model for multivariate genome-wide association studies that handles incomplete data and reduces computational complexity.

bioRxiv · Feb 21, 2022 · PreprintBioinformatics

Rapid Epistatic Mixed Model Association Studies by Controlling Multiple Polygenic Effects

Dan Wang, Hui Tang, Jianfeng Liu, Shizhong Xu, Qin Zhang, Chao Ning

The paper introduces a rapid mixed model for genome-wide epistatic association analysis that handles multiple polygenic effects and demonstrates its efficiency on yeast and human datasets.

Bioinformatics · Jun 24, 2020Peer-reviewedBioinformatics