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Updated: Apr 19, 2026

A Web-Based Workflow for Selecting Gene- and Tissue-Specific Enhancers

A Web-Based Workflow for Selecting Gene- and Tissue-Specific Enhancers

Published on: July 18, 2025

solGS: a web-based tool for genomic selection.

Isaak Y Tecle¹, Jeremy D Edwards, Naama Menda

¹Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY, USA. iyt2@cornell.edu.

BMC Bioinformatics

|December 16, 2014

Summary

This summary is machine-generated.

Genomic selection (GS) offers improved breeding accuracy but faces data challenges. We developed solGS, a web tool simplifying genomic estimated breeding value (GEBV) prediction and data sharing for breeders.

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Area of Science:

Agricultural Science
Bioinformatics
Genetics

Background:

Genomic selection (GS) enhances breeding value prediction and genetic gain for quantitative traits.
High-throughput markers and complex statistics pose data management and analysis challenges.
A bioinformatics infrastructure and user-friendly tools are crucial for practical GS implementation.

Purpose of the Study:

To develop a web-based tool for practical genomic selection.
To simplify the prediction of genomic estimated breeding values (GEBVs).
To facilitate data management, analysis, and sharing in breeding programs.

Main Methods:

Developed solGS, a web-based tool utilizing a Ridge-Regression Best Linear Unbiased Predictor (RR-BLUP) model.
Implemented an intuitive interface for training population selection and GEBV estimation.
Integrated the Chado Natural Diversity database schema for generic data storage.

Main Results:

solGS enables online prediction of GEBVs with an interactive workflow.
The tool estimates phenotypic correlation, heritability, and selection indices.
Analysis outputs are visualized graphically and available for download.

Conclusions:

solGS provides breeders with an intuitive online platform for data storage and GEBV estimation.
The tool streamlines genomic selection workflows.
solGS is adaptable to various breeding programs.