Cargando…
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...
Autores principales: | , , |
---|---|
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 |
_version_ | 1784632514770370560 |
---|---|
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. |
format | Online Article Text |
id | pubmed-8756188 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT vogtfrank vcf2gwaspythonapiforcomprehensivegwasanalysisusinggemma AT shirsekargautam vcf2gwaspythonapiforcomprehensivegwasanalysisusinggemma AT weigeldetlef vcf2gwaspythonapiforcomprehensivegwasanalysisusinggemma |