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Journal Article

vcf2gwas: python API for comprehensive GWAS analysis using GEMMA

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Vogt,  F
Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society;

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Shirsekar,  G
Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society;

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Weigel,  D
Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society;

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Citation

Vogt, F., Shirsekar, G., & Weigel, D. (2021). vcf2gwas: python API for comprehensive GWAS analysis using GEMMA. Bioinformatics, 38(3), 839-840. doi:10.1093/bioinformatics/btab710.


Cite as: https://hdl.handle.net/21.11116/0000-000A-8EC8-5
Abstract
Motivation: Genome-wide association study (GWAS) requires a researcher to perform a multitude of different actions during analysis. From editing and formatting genotype and phenotype information to running the analysis software to summarizing and visualizing the results. A typical GWAS workflow poses a significant challenge of utilizing the command-line, manual text-editing and requiring knowledge of one or more programming/scripting languages, especially for newcomers.

Results: vcf2gwas is a package that provides a convenient pipeline to perform all of the steps of a traditional GWAS workflow by reducing it to a single command-line input of a Variant Call Format (VCF) file and a phenotype data file. Additionally, all the required software is installed with the package. vcf2gwas also implements several useful features enhancing the reproducibility of GWAS analysis.

Availability and implementation: The source code of vcf2gwas is available under the GNU General Public License. The package can be easily installed using conda. Installation instructions and a manual including tutorials can be accessed on the package website at https://github.com/frankvogt/vcf2gwas.