G2P datasets: a hub for genomic datasets for predictive modeling in plants and animals

Area of Science:

• Genetics
• Bioinformatics
• Data Science

Background:

• Genomic and phenotypic data are crucial for understanding traits in plants and animals.
• Accessing and integrating diverse genomic datasets from various publications can be challenging for researchers.

Purpose of the Study:

• To introduce G2P Datasets, a novel, open-access repository for plant and animal genomic data.
• To facilitate genome-to-phenotype research by providing a unified and navigable platform for genomic and phenotypic metadata.

Main Methods:

• Compiled over 100 public genomic datasets from diverse scientific publications.
• Developed a web application interface with a searchable metadata database.
• Provided scripts for downloading and integrating datasets into an R environment.
• Integrated with Kaggle for broader data accessibility.

Main Results:

• G2P Datasets hosts over 100 curated genomic datasets for more than 60 plant and animal species.
• The repository includes metadata with DOIs and R-scripts for data access.
• A searchable database allows filtering by species, traits, and sample sizes.
• Datasets are accessible via web app, Kaggle, and direct download links.

Conclusions:

• G2P Datasets enhances accessibility and usability of public genomic data.
• The repository streamlines genome-to-phenotype research for a wide range of species.
• Encourages community contribution through an online submission form and GitHub integration.