synbreed: a framework for the analysis of genomic prediction data using R.

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• Genomic prediction is crucial for breeding programs.
• High-throughput genotyping and large-scale phenotyping generate vast datasets.
• Existing software may lack user-friendliness for complex genomic analyses.

Purpose of the Study:

• To introduce synbreed, a novel R package for genomic prediction.
• To provide a comprehensive and unified software solution for genetic analyses.
• To facilitate next-generation genetics research and education.

Main Methods:

• Development of an R package (synbreed) integrating data processing, visualization, and analysis.
• Implementation of functions for fitting and cross-validating genomic prediction models.
• Design of a unified data object to streamline the analysis pipeline.

Main Results:

• synbreed offers a versatile pipeline for genomic prediction analyses.
• The package supports a wide range of data formats and models.
• It provides a user-friendly interface for complex genetic data.

Conclusions:

• synbreed addresses the need for accessible software in modern genetics.
• The package enables efficient genome-based predictions from large datasets.
• It serves as a valuable tool for both research and educational purposes.