Epi-Gene: An R-Package for Easy Pan-Genome Analysis

Area of Science:

• Bioinformatics
• Genomics
• Computational Biology

Background:

• Analyzing large genomic datasets presents significant computational challenges, including time consumption and memory requirements.
• Existing tools may lack efficiency or require advanced programming skills for handling extensive sequence data.

Purpose of the Study:

• To develop and present Epi-gene, an R-package designed for efficient analysis of large genomic datasets.
• To demonstrate Epi-gene's capabilities in handling large sequence files and reducing computational time.

Main Methods:

• The study utilized the Epi-gene R-package, which includes functions for joining, relabeling, and converting FASTA formatted sequences.
• Epi-gene functions were employed to identify core, accessory, and unique genes within a dataset of 14 *Aeromonas hydrophila* genomes.
• Analysis involved constructing heat maps and phylogenetic genome trees, integrating functions from R packages like dplyr and ggtree.

Main Results:

• The Epi-gene R-package successfully analyzed genomic data, completing complex procedures in under 30 minutes.
• The package demonstrated efficient handling of large sequence files and reduced the need for extensive programming expertise.
• Core, accessory, and unique gene subsets were effectively calculated and visualized.

Conclusions:

• Epi-gene offers a time- and memory-efficient solution for analyzing large-scale genomic data, particularly for researchers working with multiple genomes.
• The R-package simplifies complex genomic analyses, making them more accessible with less programming skill.
• While effective, the current version of Epi-gene is limited to Windows operating systems.