Literature DB >> 18613097

CANDID: a flexible method for prioritizing candidate genes for complex human traits.

Janna E Hutz1, Aldi T Kraja, Howard L McLeod, Michael A Province.   

Abstract

Genomewide studies and localized candidate gene approaches have become everyday study designs for identifying polymorphisms in genes that influence complex human traits. Yet, in general, the number of significant findings and the need to focus on smaller regions require a prioritization of genes for further study. Some candidate gene identification algorithms have been proposed in recent years to attempt to streamline this prioritization, but many suffer from limitations imposed by the source data or are difficult to use and understand. CANDID is a prioritization algorithm designed to produce impartial, accurate rankings of candidate genes that influence complex human traits. CANDID can use information from publications, protein domain descriptions, cross-species conservation measures, gene expression profiles and protein-protein interactions in its analysis. Additionally, users may supplement these data sources with results from linkage, association and other studies. CANDID was tested on well-known complex trait genes using data from the Online Mendelian Inheritance in Man database. Additionally, CANDID was evaluated in a modeled gene discovery environment, where it ranked genes whose trait associations were published after CANDID's databases were compiled. In all settings, CANDID exhibited high sensitivity and specificity, indicating an improvement upon previously published algorithms. Its accuracy and ease of use make CANDID a highly useful tool in study design and analysis for complex human traits.

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Year:  2008        PMID: 18613097      PMCID: PMC4420475          DOI: 10.1002/gepi.20346

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  72 in total

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10.  Newly identified loci that influence lipid concentrations and risk of coronary artery disease.

Authors:  Cristen J Willer; Serena Sanna; Anne U Jackson; Angelo Scuteri; Lori L Bonnycastle; Robert Clarke; Simon C Heath; Nicholas J Timpson; Samer S Najjar; Heather M Stringham; James Strait; William L Duren; Andrea Maschio; Fabio Busonero; Antonella Mulas; Giuseppe Albai; Amy J Swift; Mario A Morken; Narisu Narisu; Derrick Bennett; Sarah Parish; Haiqing Shen; Pilar Galan; Pierre Meneton; Serge Hercberg; Diana Zelenika; Wei-Min Chen; Yun Li; Laura J Scott; Paul A Scheet; Jouko Sundvall; Richard M Watanabe; Ramaiah Nagaraja; Shah Ebrahim; Debbie A Lawlor; Yoav Ben-Shlomo; George Davey-Smith; Alan R Shuldiner; Rory Collins; Richard N Bergman; Manuela Uda; Jaakko Tuomilehto; Antonio Cao; Francis S Collins; Edward Lakatta; G Mark Lathrop; Michael Boehnke; David Schlessinger; Karen L Mohlke; Gonçalo R Abecasis
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  40 in total

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3.  Integrative pathway analysis of a genome-wide association study of (V)O(2max) response to exercise training.

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Review 4.  Candidate gene prioritization.

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Journal:  Mol Genet Genomics       Date:  2012-08-15       Impact factor: 3.291

Review 5.  Genome-wide association studies and the genetic dissection of complex traits.

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6.  Mind the dbGAP: the application of data mining to identify biological mechanisms.

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7.  Genomic convergence of genome-wide investigations for complex traits.

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8.  Application of gene network analysis techniques identifies AXIN1/PDIA2 and endoglin haplotypes associated with bicuspid aortic valve.

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