OrdinalGWAS.jl

Genome-wide association studies (GWAS) for ordered categorical phenotypes
Author OpenMendel
Popularity
8 Stars
Updated Last
1 Year Ago
Started In
April 2018

OrdinalGWAS

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OrdinalGWAS.jl is a Julia package for performing genome-wide association studies (GWAS) for ordered categorical phenotypes. It is useful when the phenotype takes ordered discrete values, e.g., disease status (undiagnosed, pre-disease, mild, moderate, severe). It runs efficiently and scales well to very large datasets. The package currently supports PLINK, VCF (both dosage and genotype data) file formats, and BGEN file formats. We plan to add PGEN support in the future.

OrdinalGWAS.jl supports Julia v1.5 or later. See the documentation for usage.

OrdinalGWAS.jl is not yet registered. It requires SnpArrays.jl, VCFTools.jl, BGEN.jl, and OrdinalMultinomialModels.jl which are also not yet registered, so it will require the following steps to install. Start julia and use the ] key to switch to the package manager REPL and run:

pkg> add https://github.com/OpenMendel/SnpArrays.jl

pkg> add https://github.com/OpenMendel/VCFTools.jl

pkg> add https://github.com/OpenMendel/BGEN.jl

pkg> add https://github.com/OpenMendel/OrdinalMultinomialModels.jl

pkg> add https://github.com/OpenMendel/OrdinalGWAS.jl

Citation

The methods and applications of this software package are detailed in the following publication:

German CA, Sinsheimer JS, Klimentidis YC, Zhou H, Zhou JJ. (2020) Ordered multinomial regression for genetic association analysis of ordinal phenotypes at Biobank scale. Genetic Epidemiology. 44:248-260. https://doi.org/10.1002/gepi.22276

If you use OpenMendel analysis packages in your research, please cite the following reference in the resulting publications:

OPENMENDEL: a cooperative programming project for statistical genetics. Zhou H, Sinsheimer JS, Bates DM, Chu BB, German CA, Ji SS, Keys KL, Kim J, Ko S, Mosher GD, Papp JC, Sobel EM, Zhai J, Zhou JJ, Lange K. Hum Genet. 2019 Mar 26. doi: 10.1007/s00439-019-02001-z. [Epub ahead of print] PMID: 30915546

Acknowledgments

This project is supported by the National Institutes of Health under NIGMS awards R01GM053275 and R25GM103774 and NHGRI award R01HG006139.