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Ranking candidate genes in rat models of type 2 diabetes
University of Borås, School of Health Science.
2009 (English)In: Theoretical Biology Medical Modelling, ISSN 1742-4682, E-ISSN 1742-4682, Vol. 6, no 12Article in journal (Refereed) Published
Abstract [en]

Background Rat models are frequently used to find genomic regions that contribute to complex diseases, so called quantitative trait loci (QTLs). In general, the genomic regions found to be associated with a quantitative trait are rather large, covering hundreds of genes. To help selecting appropriate candidate genes from QTLs associated with type 2 diabetes models in rat, we have developed a web tool called Candidate Gene Capture (CGC), specifically adopted for this disorder. Methods CGC combines diabetes-related genomic regions in rat with rat/human homology data, textual descriptions of gene effects and an array of 789 keywords. Each keyword is assigned values that reflect its co-occurrence with 24 different reference terms describing sub-phenotypes of type 2 diabetes (for example "insulin resistance"). The genes are then ranked based on the occurrences of keywords in the describing texts. Results CGC includes QTLs from type 2 diabetes models in rat. When comparing gene rankings from CGC based on one sub-phenotype, with manual gene ratings for four QTLs, very similar results were obtained. In total, 24 different sub-phenotypes are available as reference terms in the application and based on differences in gene ranking, they fall into separate clusters. Conclusion The very good agreement between the CGC gene ranking and the manual rating confirms that CGC is as a reliable tool for interpreting textual information. This, together with the possibility to select many different sub-phenotypes, makes CGC a versatile tool for finding candidate genes. CGC is publicly available at http://ratmap.org/CGC.

Place, publisher, year, edition, pages
BioMed Central Ltd. , 2009. Vol. 6, no 12
Keywords [en]
rats, genomics, Genetics medicine
National Category
Medical Genetics
Identifiers
URN: urn:nbn:se:hb:diva-2771DOI: 10.1186/1742-4682-6-12Local ID: 2320/6039OAI: oai:DiVA.org:hb-2771DiVA, id: diva2:870865
Note

Sponsorship:

Swedish Medical Research Council, the Nilsson-Ehle Foundation, the Sven and Lilly Lawski Foundation, the Erik Philip-Sorensen Foundation, the Wilhelm and Martina Lundgren Research Foundation, and the SWEGENE Foundation.

Available from: 2015-11-13 Created: 2015-11-13 Last updated: 2018-01-10Bibliographically approved

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Ståhl, Fredrik

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