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Disease gene prediction database

Wouters, Merridee, Oti, Martin and Ballouz, Sara 2012, Disease gene prediction database [data collection], Development of a bioinformatic tool for the rapid identification of candidate disease genes, RM23392.

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Name Description MIMEType Size Downloads

Field of Research 060499 Genetics not elsewhere classified
Socio Economic Objective 920110 Inherited Diseases (incl. Gene Therapy)
Name of data collection Disease gene prediction database
Alternative title Gentrepid gene predictions for human diseases based on published Genome-Wide Association Studies database
Gentrepid-GWA database
Creator(s) Wouters, Merridee
Oti, Martin
Ballouz, Sara
Related institution(s) HuGE
Victor Chang Cardiac Research Institute
Date completed 2012
Material type database
ANDS collection type dataset
Collection start date 2010-01-01
Collection end date 2012-12-31
Project name Development of a bioinformatic tool for the rapid identification of candidate disease genes
Project Description This project provides a repository for candidate genes predicted by the Gentrepid software suite based on public genome-wide association data.

Genome-wide association studies (GWAS) are population based studies that associate genetic signals with phenotypes at a much finer mapping level than linkage studies. Surprisingly few genes and molecular mechanisms have been implicated as disease “culprits” for complex diseases by GWAS. The genetic data has turned out to be less statistically powerful than originally hoped and the original data analysis methods employed were likely not sophisticated enough. Nonetheless, this data is a valuable resource which has been archived by the National Centre for Biotechnology Information (NCBI, USA) in the HuGe database. In the hope that reanalysis of the data with new techniques will yield more information about these disease. We recently developed novel protocols which address the effects of noise in the data and genomic architecture and processed the data with Gentrepid: a bioinformatic tool which utilizes domain-based and pathway-based functional information to make predictions. We are systematically re-analysing the data in HuGe

Project ID RM23392
Description of resource 100 MB, 50 items
Keyword(s) database
genetic databases
protein disease/genetics
genome-wide association study
single nucleotide
Language eng
Summary This database includes gene predictions for disease phenotypes based on published Genome-Wide Association Data. May be used to choose primers for phenotype-specific resquencing of patient DNA.
For each prediction for following data is listed: phenotype, predicted gene, significant SNP, datasource, datasource reference.
GrantID NHMRC 635512
General notes The data was generated by a computer from clinical data, and some data from HuGE ( was used. The data is organised within a searchable website.
Contact details (email)
Contact details (physical) School of Life and Environmental Sciences, Deakin University, 75 Pigdons Road, Waurn Ponds, Victoria 3216 Australia
Access conditions Data is open to all for private study and fair use only.
Related work DU:30043895
Persistent URL

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Created: Wed, 28 Mar 2012, 10:00:21 EST by Lesa Maclean

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