English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  vcf2gwas: python API for comprehensive GWAS analysis using GEMMA

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.

Item is

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Vogt, F1, Author           
Shirsekar, G1, Author           
Weigel, D1, Author           
Affiliations:
1Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society, ou_3375790              

Content

show
hide
Free keywords: -
 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.

Details

show
hide
Language(s):
 Dates: 2021-10
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1093/bioinformatics/btab710
PMID: 34636840
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Bioinformatics
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Oxford : Oxford University Press
Pages: - Volume / Issue: 38 (3) Sequence Number: - Start / End Page: 839 - 840 Identifier: ISSN: 1367-4803
CoNE: https://pure.mpg.de/cone/journals/resource/954926969991