ShiNyP: Unlocking SNP-Based Population Genetics-AI-Assisted Platform for Rapid and Interactive Visual Exploration

Area of Science:

• Genomics
• Bioinformatics
• Evolutionary Biology

Background:

• Genome-wide single nucleotide polymorphism (SNP) data analysis is crucial for molecular biology, evolutionary genetics, and breeding.
• Existing analytical pipelines are often fragmented and require advanced computational skills, hindering accessibility.
• A need exists for integrated, user-friendly tools for comprehensive SNP data analysis.

Purpose of the Study:

• To introduce ShiNyP, an interactive R/Shiny platform designed to streamline population genomics research.
• To provide a unified interface for the entire SNP analysis workflow, from data import to advanced population genetics analyses.
• To enhance the accessibility and reproducibility of complex genomic data analysis for a broader research community.

Main Methods:

• Development of an interactive R/Shiny application integrating multiple SNP analysis modules.
• Implementation of functionalities for data import, quality control, population structure inference, diversity analysis, and selective scan.
• Inclusion of automated generation of visualizations and summary tables, and an AI-powered reporting module.
• Support for haploid, diploid, and polyploid species data.

Main Results:

• ShiNyP provides a single, intuitive interface for diverse population genomics analyses.
• The platform automates the creation of over 70 publication-ready figures and tables.
• An AI-driven module generates interpretable narratives for complex statistical results.
• Performance tests confirm efficient processing of large datasets on standard hardware.

Conclusions:

• ShiNyP significantly enhances the accessibility and efficiency of population genomics research.
• The platform democratizes the analysis of single nucleotide polymorphism data through an integrated and user-friendly approach.
• ShiNyP offers a reproducible and powerful solution for researchers in molecular biology, evolutionary genetics, and breeding.