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dc.creatorZintzaras, E.en
dc.creatorLau, J.en
dc.date.accessioned2015-11-23T10:55:15Z
dc.date.available2015-11-23T10:55:15Z
dc.date.issued2008
dc.identifier10.1007/s10038-007-0223-5
dc.identifier.issn1434-5161
dc.identifier.urihttp://hdl.handle.net/11615/34968
dc.description.abstractThe number of published genetic association studies (GASs) is increasing tremendously due to the availability of mapped single-nucleotide polymorphisms (SNPs) and advances in genotyping technologies. A search in HuGENet illustrates the rapid accumulation of evidence for major diseases. Recently, there has been a lot of activity regarding genome-wide association studies (GWASs), and a growing number of forthcoming studies is expected. GASs and GWASs are usually underpowered to detect significant associations, and the varying quality of reporting publications befuddles researchers. A meta-analysis can increase power and provide standards of reporting results. However, the conduct of a meta-analysis of GASs faces a major obstacle, which is the structure and diversity of stored information in databases. Similar problems are expected for GWASs, though the data are not yet publicly available. The development of a Web-based system for the detailed and structured recording of GAS or GWAS data, accompanied by an estimation of the overall genetic risk effects, would enable scientists to keep track of evidence for gene-disease associations.en
dc.sourceJournal of Human Geneticsen
dc.source.uri<Go to ISI>://WOS:000251827900001
dc.subjectmeta-analysisen
dc.subjectepidemiologyen
dc.subjectgeneticsen
dc.subjectgenomicsen
dc.subjectpolymorphismen
dc.subjectassociationen
dc.subjectdatabaseen
dc.subjectqualityen
dc.subjectMETHYLENETETRAHYDROFOLATE REDUCTASE GENEen
dc.subjectRANDOMIZED CONTROLLED-TRIALSen
dc.subjectNEUROTROPHIC FACTOR GENEen
dc.subjectGENOME-WIDE ASSOCIATIONen
dc.subjectPOPULATIONen
dc.subjectSTRATIFICATIONen
dc.subjectDIABETIC-NEPHROPATHYen
dc.subjectPARKINSONS-DISEASEen
dc.subjectPOLYMORPHISMSen
dc.subjectRISKen
dc.subjectSTATEMENTen
dc.subjectGenetics & Heredityen
dc.titleTrends in meta-analysis of genetic association studiesen
dc.typejournalArticleen


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