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Updated: May 8, 2026
09:34
Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
Published on: April 4, 2018
Gentrepid V2.0: a web server for candidate disease gene prediction.
Sara Ballouz1, Jason Y Liu, Richard A George
1School of Medicine, Deakin University, Geelong, VIC 3217, Australia. m.wouters@deakin.edu.au.
BMC Bioinformatics
|August 17, 2013
Summary
Gentrepid predicts candidate disease genes using protein pathway and domain information. This bioinformatics tool aids in understanding disease mechanisms and analyzing genome-wide association studies (GWAS) for complex diseases.
Area of Science:
- Bioinformatics
- Genomics
- Computational Biology
Background:
- Candidate disease gene prediction is crucial for advancing human health.
- Increasing experimental data necessitates improved bioinformatics tools for disease gene discovery.
Purpose of the Study:
- To present Gentrepid, a web resource for predicting and prioritizing candidate disease genes.
- To enhance the analysis of genome-wide association studies (GWAS) data for complex diseases.
Main Methods:
- Gentrepid integrates data from diverse gene and protein resources.
- It utilizes known disease gene information (OMIM) to identify genes in shared protein pathways or domains.
- An ab initio approach detects enriched protein annotations without prior phenotype knowledge.
Main Results:
- The updated Gentrepid system facilitates GWAS data analysis for complex diseases.
- An example application to hypertension GWAS data identified a novel ZIP transporter prediction.
- The system successfully integrates phenotype/genotype information with protein data.
Conclusions:
- Gentrepid aids in understanding the biological mechanisms underlying diseases.
- The tool supports the discovery of novel disease-associated genes.
- The webserver is available at https://www.gentrepid.org/ for public use.
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