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.
Attached Files
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
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 Nonetheless, this data is a valuable resource which has been archived by the National Centre for Biotechnology Information (NCBI, USA) in the HuGe database.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
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 (http://hugenavigator.net/HuGENavigator/home.do) was used. The data is organised within a searchable website.
Contact details (email)
m.wouters@deakin.edu.au
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.
Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.
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