ShinyGAStool: A user-friendly tool for candidate gene association studies

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• Analyzing genotyping and sequencing data is often hindered by complex bioinformatics tools.
• There is a need for user-friendly solutions to facilitate genetic association studies.

Purpose of the Study:

• To develop an accessible, open-source tool for candidate gene association analysis.
• To simplify the process of linking genetic variants to phenotypes using large datasets.

Main Methods:

• Developed shinyGAStool, a web-browser based application.
• Implemented a 3-step workflow: data exploration, gene/variant selection, and association analysis.
• The tool is designed for ease of use with large genetic datasets.

Main Results:

• shinyGAStool provides an intuitive interface for exploring phenotype and covariate distributions.
• Users can efficiently select relevant genes and variants for analysis.
• The tool facilitates the execution of association analyses linking genetic data with phenotypic traits.

Conclusions:

• shinyGAStool significantly lowers the barrier to performing candidate gene association studies.
• This tool empowers researchers to analyze large genetic datasets more effectively.
• Open-source accessibility promotes wider adoption and collaboration in genetic research.