A versatile gene-based test for genome-wide association studies

Jimmy Z. Liu, Allan F McRae, Dale R. Nyholt, Sarah E. Medland, Naomi R Wray, Kevin M. Brown, Nicholas K. Hayward, Grant W. Montgomery, Peter M. Visscher, Nicholas G. Martin, Stuart MacGregor, AMFS Investigators

Research output: Contribution to journalArticlepeer-review

569 Citations (Scopus)

Abstract

We have derived a versatile gene-based test for genome-wide association studies (GWAS). Our approach, called VEGAS (versatile gene-based association study), is applicable to all GWAS designs, including family-based GWAS, meta-analyses of GWAS on the basis of summary data, and DNA-pooling-based GWAS, where existing approaches based on permutation are not possible, as well as singleton data, where they are. The test incorporates information from a full set of markers (or a defined subset) within a gene and accounts for linkage disequilibrium between markers by using simulations from the multivariate normal distribution. We show that for an association study using singletons, our approach produces results equivalent to those obtained via permutation in a fraction of the computation time. We demonstrate proof-of-principle by using the gene-based test to replicate several genes known to be associated on the basis of results from a family-based GWAS for height in 11,536 individuals and a DNA-pooling-based GWAS for melanoma in approximately 1300 cases and controls. Our method has the potential to identify novel associated genes; provide a basis for selecting SNPs for replication; and be directly used in network (pathway) approaches that require per-gene association test statistics. We have implemented the approach in both an easy-to-use web interface, which only requires the uploading of markers with their association p-values, and a separate downloadable application.

Original languageEnglish
Pages (from-to)139-45
Number of pages7
JournalAmerican Journal of Human Genetics
Volume87
Issue number1
DOIs
Publication statusPublished - 9 Jul 2010
Externally publishedYes

Keywords

  • Case-Control Studies
  • Genetic Markers
  • Genome-Wide Association Study
  • Humans
  • Melanoma
  • Meta-Analysis as Topic
  • Multivariate Analysis
  • Polymorphism, Single Nucleotide
  • Skin Neoplasms
  • Journal Article
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

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