Abstract:
:The advent of genome-wide association studies has allowed considerable progress in the identification and robust replication of common gene variants that confer susceptibility to common diseases and other phenotypes of interest. These genetic effect sizes are almost invariably moderate to small in magnitude and single studies, even if large, are underpowered to detect them with confidence. Meta-analysis of many genome-wide association studies improves the power to detect more associations, and to investigate the consistency or heterogeneity of these associations across diverse datasets and study populations. In this review, we discuss the key methodological issues in the set-up, information gathering and processing, and analysis of meta-analyses of genome-wide association datasets. We illustrate, as an example, the application of meta-analysis methods in the elucidation of common genetic variants associated with Type 2 diabetes. Finally, we discuss the prospects and caveats for future application of meta-analysis methods in the genome-wide setting.
journal_name
Pharmacogenomicsjournal_title
Pharmacogenomicsauthors
Zeggini E,Ioannidis JPdoi
10.2217/14622416.10.2.191subject
Has Abstractpub_date
2009-02-01 00:00:00pages
191-201issue
2eissn
1462-2416issn
1744-8042pii
10.2217/14622416.10.2.191journal_volume
10pub_type
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