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A Versatile Gene-Based Test for Genome-wide Association Studies

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,... Full description

Journal Title: American journal of human genetics 2010-07-09, Vol.87 (1), p.139-145
Main Author: Liu, Jimmy Z
Other Authors: Mcrae, Allan F , Nyholt, Dale R , Medland, Sarah E , Wray, Naomi R , Brown, Kevin M , Hayward, Nicholas K , Montgomery, Grant W , Visscher, Peter M , Martin, Nicholas G , Macgregor, Stuart
Format: Electronic Article Electronic Article
Language: English
Subjects:
DNA
Quelle: Alma/SFX Local Collection
Publisher: Cambridge, MA: Elsevier Inc
ID: ISSN: 0002-9297
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recordid: cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_2896770
title: A Versatile Gene-Based Test for Genome-wide Association Studies
format: Article
creator:
  • Liu, Jimmy Z
  • Mcrae, Allan F
  • Nyholt, Dale R
  • Medland, Sarah E
  • Wray, Naomi R
  • Brown, Kevin M
  • Hayward, Nicholas K
  • Montgomery, Grant W
  • Visscher, Peter M
  • Martin, Nicholas G
  • Macgregor, Stuart
subjects:
  • Analysis
  • Biological and medical sciences
  • Biomarkers
  • Case-Control Studies
  • Deoxyribonucleic acid
  • DNA
  • DNA replication
  • Fundamental and applied biological sciences. Psychology
  • Gene mutations
  • General aspects. Genetic counseling
  • Genes
  • Genetic Markers
  • Genetics
  • Genetics of eukaryotes. Biological and molecular evolution
  • Genetics(clinical)
  • Genome-Wide Association Study - methods
  • Genomics
  • Human genome
  • Humans
  • Medical genetics
  • Medical sciences
  • Melanoma - genetics
  • Meta-Analysis as Topic
  • Molecular and cellular biology
  • Multivariate Analysis
  • Polymorphism, Single Nucleotide
  • Report
  • Simulation
  • Single nucleotide polymorphisms
  • Skin Neoplasms - genetics
ispartof: American journal of human genetics, 2010-07-09, Vol.87 (1), p.139-145
description: 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 ∼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.
language: eng
source: Alma/SFX Local Collection
identifier: ISSN: 0002-9297
fulltext: fulltext
issn:
  • 0002-9297
  • 1537-6605
url: Link


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creatorLiu, Jimmy Z ; Mcrae, Allan F ; Nyholt, Dale R ; Medland, Sarah E ; Wray, Naomi R ; Brown, Kevin M ; Hayward, Nicholas K ; Montgomery, Grant W ; Visscher, Peter M ; Martin, Nicholas G ; Macgregor, Stuart
creatorcontribLiu, Jimmy Z ; Mcrae, Allan F ; Nyholt, Dale R ; Medland, Sarah E ; Wray, Naomi R ; Brown, Kevin M ; Hayward, Nicholas K ; Montgomery, Grant W ; Visscher, Peter M ; Martin, Nicholas G ; Macgregor, Stuart ; AMFS Investigators
descriptionWe 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 ∼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.
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subjectAnalysis ; Biological and medical sciences ; Biomarkers ; Case-Control Studies ; Deoxyribonucleic acid ; DNA ; DNA replication ; Fundamental and applied biological sciences. Psychology ; Gene mutations ; General aspects. Genetic counseling ; Genes ; Genetic Markers ; Genetics ; Genetics of eukaryotes. Biological and molecular evolution ; Genetics(clinical) ; Genome-Wide Association Study - methods ; Genomics ; Human genome ; Humans ; Medical genetics ; Medical sciences ; Melanoma - genetics ; Meta-Analysis as Topic ; Molecular and cellular biology ; Multivariate Analysis ; Polymorphism, Single Nucleotide ; Report ; Simulation ; Single nucleotide polymorphisms ; Skin Neoplasms - genetics
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descriptionWe 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 ∼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.
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abstractWe 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 ∼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.
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doi10.1016/j.ajhg.2010.06.009
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