Visual Integration of Genome-Wide Association Studies and Differential Expression Results with the Hidecan R Package

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• Genome-wide association studies (GWAS) and differential expression analyses are crucial for understanding genetic traits.
• Visualizing results from these complex analyses, especially for polyploid organisms, presents a significant challenge.
• Integrating manually curated candidate genes enhances biological interpretation.

Purpose of the Study:

• To introduce hidecan, an R package designed for comprehensive visualization of GWAS and differential expression analysis results.
• To provide functionalities specifically tailored for visualizing GWAS data from autotetraploid organisms using the GWASpoly package.
• To offer a versatile tool applicable across all ploidy levels for summarizing and exploring genetic analysis outcomes.

Main Methods:

• Development of an R package, hidecan, implementing advanced visualization techniques.
• Integration of functionalities to process and display results from multiple GWAS and differential expression analyses.
• Inclusion of methods to incorporate manually curated candidate genes alongside statistical findings.

Main Results:

• The hidecan package effectively visualizes summarized results from genetic analyses.
• Demonstrated utility with two autotetraploid potato datasets, showcasing its capability for complex organisms.
• Successful integration with GWASpoly for autotetraploid GWAS data visualization.

Conclusions:

• hidecan is a publicly available R package on CRAN and GitHub, facilitating genetic data exploration.
• A comprehensive tutorial and package description are provided for user guidance.
• hidecan is part of the VIEWpoly tool, enhancing visualization and exploration of polyploid computational results.