Journal
AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS
Volume 168, Issue 7, Pages 517-527Publisher
WILEY
DOI: 10.1002/ajmg.b.32328
Keywords
genome-wide association studies; polygenic effects; gene set analysis; complex traits
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Funding
- NIMH [R01MH099064]
- NIH/NCATS [UL1TR000128]
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To maximize the potential of genome-wide association studies, many researchers are performing secondary analyses to identify sets of genes jointly associated with the trait of interest. Although methods for gene-set analyses (GSA), also called pathway analyses, have been around for more than a decade, the field is still evolving. There are numerous algorithms available for testing the cumulative effect of multiple SNPs, yet no real consensus in the field about the best way to perform a GSA. This paper provides an overview of the factors that can affect the results of a GSA, the lessons learned from past studies, and suggestions for how to make analysis choices that are most appropriate for different types of data. (c) 2015 Wiley Periodicals, Inc.
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