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vcf2gwas: Python API for comprehensive GWAS analysis using GEMMA

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 pose...

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Detalles Bibliográficos
Autores principales: Vogt, Frank, Shirsekar, Gautam, Weigel, Detlef
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8756188/
https://www.ncbi.nlm.nih.gov/pubmed/34636840
http://dx.doi.org/10.1093/bioinformatics/btab710
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author Vogt, Frank
Shirsekar, Gautam
Weigel, Detlef
author_facet Vogt, Frank
Shirsekar, Gautam
Weigel, Detlef
author_sort Vogt, Frank
collection PubMed
description 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 file and a phenotype data file. In addition, 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. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-87561882022-01-13 vcf2gwas: Python API for comprehensive GWAS analysis using GEMMA Vogt, Frank Shirsekar, Gautam Weigel, Detlef Bioinformatics Applications Notes 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 file and a phenotype data file. In addition, 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. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-10-12 /pmc/articles/PMC8756188/ /pubmed/34636840 http://dx.doi.org/10.1093/bioinformatics/btab710 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Vogt, Frank
Shirsekar, Gautam
Weigel, Detlef
vcf2gwas: Python API for comprehensive GWAS analysis using GEMMA
title vcf2gwas: Python API for comprehensive GWAS analysis using GEMMA
title_full vcf2gwas: Python API for comprehensive GWAS analysis using GEMMA
title_fullStr vcf2gwas: Python API for comprehensive GWAS analysis using GEMMA
title_full_unstemmed vcf2gwas: Python API for comprehensive GWAS analysis using GEMMA
title_short vcf2gwas: Python API for comprehensive GWAS analysis using GEMMA
title_sort vcf2gwas: python api for comprehensive gwas analysis using gemma
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8756188/
https://www.ncbi.nlm.nih.gov/pubmed/34636840
http://dx.doi.org/10.1093/bioinformatics/btab710
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