BioinformaticsBioinformaticsPeer-reviewed journal article
vcf2gwas - Python API for comprehensive GWAS analysis using GEMMA
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Abstract
We present a new software package vcf2gwas to perform reproducible genome-wide association studies (GWAS). vcf2gwas is a Python API for bcftools, PLINK and GEMMA. Before running the analysis a traditional GWAS workflow requires the user to edit and format the genotype information from commonly used Variant Call Format (VCF) file and phenotype information. Post-processing steps involve summarizing and visualizing the analysis results. This workflow requires a user to utilize the command-line, manual text-editing and knowledge of one or more programming/scripting languages which can be time-consuming especially when analyzing multiple phenotypes. Our package provides a convenient pipeline performing all of these steps, reducing the GWAS workflow to a single command-line input without the need to edit or format the VCF file beforehand or to install any additional software. In addition, features like reducing the dimensionality of the phenotypic space and performing analyses on the reduced dimensions or comparing the significant variants from the results to specific genes/regions of interest are implemented. By integrating different tools to perform GWAS under one workflow, the package ensures reproducible GWAS while reducing the user efforts significantly. Availability and implementationThe 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
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- research focus: benchmarking
- research focus: software / tool
- approach: statistical model
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