fGWAS: An R package for genome-wide association analysis with longitudinal phenotypes

Zhong Wang^{a, b
, ,},
Nating Wang^a,
Rongling Wu^{c, d},
Zuoheng Wang^{e
, ,}

a.
College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
b.
Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14850, USA
c.
Center for Computational Biology, Beijing Forestry University, Beijing 100083, China
d.
Center for Statistical Genetics, Department of Public Health Sciences, Pennsylvania State College of Medicine, Hershey, PA 17033, USA
e.
Department of Biostatistics, Yale School of Public Health, New Haven, CT 06510, USA

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Corresponding author: E-mail address: zhongwang@bjfu.edu.cn (Zhong Wang); E-mail address: zuoheng.wang@yale.edu (Zuoheng Wang)

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2.	Yuan, M., Xu, X.S., Yang, Y. et al. SCEBE: An efficient and scalable algorithm for genome-wide association studies on longitudinal outcomes with mixed-effects modeling. Briefings in Bioinformatics, 2021, 22(3): bbaa130. 必应学术
3.	Gan, J., Cao, Y., Jiang, L. et al. Mapping covariation quantitative trait loci that control organ growth and whole-plant biomass. Frontiers in Plant Science, 2019. 必应学术
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doi: 10.1016/j.jgg.2018.06.006

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fGWAS: An R package for genome-wide association analysis with longitudinal phenotypes

Corresponding author: E-mail address: zhongwang@bjfu.edu.cn (Zhong Wang); E-mail address: zuoheng.wang@yale.edu (Zuoheng Wang)

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doi: 10.1016/j.jgg.2018.06.006

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fGWAS: An R package for genome-wide association analysis with longitudinal phenotypes

Corresponding author: E-mail address: zhongwang@bjfu.edu.cn (Zhong Wang); E-mail address: zuoheng.wang@yale.edu (Zuoheng Wang)

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