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385
Association analyses of 249 796 individuals reveal 18 new loci associated with body mass index
, 2010
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Practical aspects of imputation-drivenmeta-analysis of genome-wide association studies.
- Hum. Mol. Genet.
, 2008
"... Motivated by the overwhelming success of genome-wide association studies, droves of researchers are working vigorously to exchange and to combine genetic data to expediently discover genetic risk factors for common human traits. The primary tools that fuel these new efforts are imputation, allowing ..."
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Cited by 45 (4 self)
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Motivated by the overwhelming success of genome-wide association studies, droves of researchers are working vigorously to exchange and to combine genetic data to expediently discover genetic risk factors for common human traits. The primary tools that fuel these new efforts are imputation, allowing researchers who have collected data on a diversity of genotype platforms to share data in a uniformly exchangeable format, and meta-analysis for pooling statistical support for a genotype -phenotype association. As many groups are forming collaborations to engage in these efforts, this review collects a series of guidelines, practical detail and learned experiences from a variety of individuals who have contributed to the subject.
On the Use of General Control Samples for Genome-wide Association Studies: Genetic Matching Highlights Causal Variants
- THE AMERICAN JOURNAL OF HUMAN GENETICS
, 2008
"... Resources being amassed for genome-wide association (GWA) studies include "control databases" genotyped with a large-scale SNP array. How to use these databases effectively is an open question. We develop a method to match, by genetic ancestry, controls to affected individuals (cases). Th ..."
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Cited by 37 (15 self)
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Resources being amassed for genome-wide association (GWA) studies include "control databases" genotyped with a large-scale SNP array. How to use these databases effectively is an open question. We develop a method to match, by genetic ancestry, controls to affected individuals (cases). The impact of this method, especially for heterogeneous human populations, is to reduce the false-positive rate, inflate other spuriously small p values, and have little impact on the p values associated with true positive loci. Thus, it highlights true positives by downplaying false positives. We perform a GWA by matching Americans with type 1 diabetes (T1D) to controls from Germany. Despite the complex study design, these analyses identify numerous loci known to confer risk for T1D.
INVESTIGATION Genotype Imputation with Thousands of Genomes
"... ABSTRACT Genotype imputation is a statistical technique that is often used to increase the power and resolution of genetic association studies. Imputation methods work by using haplotype patterns in a reference panel to predict unobserved genotypes in a study dataset, and a number of approaches have ..."
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Cited by 34 (1 self)
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ABSTRACT Genotype imputation is a statistical technique that is often used to increase the power and resolution of genetic association studies. Imputation methods work by using haplotype patterns in a reference panel to predict unobserved genotypes in a study dataset, and a number of approaches have been proposed for choosing subsets of reference haplotypes that will maximize accuracy in a given study population. These panel selection strategies become harder to apply and interpret as sequencing efforts like the 1000 Genomes Project produce larger and more diverse reference sets, which led us to develop an alternative framework. Our approach is built around a new approximation that uses local sequence similarity to choose a custom reference panel for each study haplotype in each region of the genome. This approximation makes it computationally efficient to use all available reference haplotypes, which allows us to bypass the panel selection step and to improve accuracy at low-frequency variants by capturing unexpected allele sharing among populations. Using data from HapMap 3, we show that our framework produces accurate results in a wide range of human populations. We also use data from the Malaria Genetic Epidemiology Network (MalariaGEN) to provide recommendations for imputation-based studies in Africa. We demonstrate that our approximation improves efficiency in large, sequence-based reference panels, and we discuss general computational strategies for modern reference datasets. Genome-wide association studies will soon be able to harness the power of thousands of reference genomes, and our work provides a practical way for investigators to use this rich information. New methodology from this study is implemented in the IMPUTE2 software package.
An MCMC algorithm for haplotype assembly from whole genome sequence data
- Genome Res
, 2008
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The imprinted DLK1-MEG3 gene region on chromosome 14q32.2 alters susceptibility to type 1 diabetes. Nat Genet. 2010; 42:68–71. [PubMed
, 1996
"... Genomewide association studies to map common disease susceptibility loci have been hugely successful with over 300 reproducibly associated loci reported to date,1 but, perhaps surprisingly, have not yet provided convincing evidence for any susceptibility locus subject to parent of origin effects. We ..."
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Cited by 31 (3 self)
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Genomewide association studies to map common disease susceptibility loci have been hugely successful with over 300 reproducibly associated loci reported to date,1 but, perhaps surprisingly, have not yet provided convincing evidence for any susceptibility locus subject to parent of origin effects. We used imputation to extend existing genomewide association datasets2, 3, 4 and here report robust evidence, at rs941576, for paternally inherited risk of type 1 diabetes (T1D, ratio of allelic effects for paternal vs maternal transmissions = 0.75, 95%CI=0.71–0.79), in the imprinted region of chromosome 14q32.2, which contains a functional candidate gene, DLK1. Our meta-analysis also provided support at genomewide significance for a T1D locus at chromosome 19p13.2, with the highest association at marker rs2304256 (OR=0.86, 95%CI=0.82–0.90) in the TYK2 gene, which has previously associated with systemic lupus erythematosus.5 We used imputation to assess association with T1D across 2.6 million polymorphic SNPs from the International HapMap Project in a total of 7514 cases and 9405 controls of European ancestry from three existing genomewide association studies: WTCCC (UK)2, GAIN/NIMH (USA)3, T1DGC (UK)4 (supplementary table 1). The R package snpMatrix6
Bayesian variable selection regression for genome-wide association studies and other large-scale problems,” The Annals of Applied Statistics
, 2011
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Two independent prostate cancer risk-associated Loci at 11q13
- Cancer Epidemiol Biomarkers Prev. 2009; 18(6): 1815–20. doi: 10.1158/ 1055-9965.EPI-08-0983 PMID: 19505914
"... Single nucleotide polymorphisms (SNP) at 11q13 were recently implicated in prostate cancer risk by two genome-wide association studies and were consistently replicated in multiple study populations. To explore prostate cancer association in the regions flanking these SNPs, we genotyped 31 tagging SN ..."
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Cited by 23 (5 self)
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Single nucleotide polymorphisms (SNP) at 11q13 were recently implicated in prostate cancer risk by two genome-wide association studies and were consistently replicated in multiple study populations. To explore prostate cancer association in the regions flanking these SNPs, we genotyped 31 tagging SNPs in a f110 kb region at 11q13 in a Swedish case-control study (Cancer of the Prostate in Sweden), including 2,899 cases and 1,722 controls. We found evidence of prostate cancer association for the previously implicated SNPs includ-ing rs10896449, which we termed locus 1. In addition, multiple SNPs on the centromeric side of the region, including rs12418451, were also significantly associated with prostate cancer risk (termed locus 2). The two
E (2009) Inference of locus-specific ancestry in closely related populations. Bioinformatics 25: i213–221. doi: 10.1093/bioinformatics/btp197 PMID
"... All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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Cited by 19 (3 self)
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All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.
Meta-analysis in genome-wide association studies
- Pharmacogenomics
, 2009
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