Literature DB >> 17357074

Leveraging the HapMap correlation structure in association studies.

Noah Zaitlen1, Hyun Min Kang, Eleazar Eskin, Eran Halperin.   

Abstract

Recent high-throughput genotyping technologies, such as the Affymetrix 500k array and the Illumina HumanHap 550 beadchip, have driven down the costs of association studies and have enabled the measurement of single-nucleotide polymorphism (SNP) allele frequency differences between case and control populations on a genomewide scale. A key aspect in the efficiency of association studies is the notion of "indirect association," where only a subset of SNPs are collected to serve as proxies for the uncollected SNPs, taking advantage of the correlation structure between SNPs. Recently, a new class of methods for indirect association, multimarker methods, has been proposed. Although the multimarker methods are a considerable advancement, current methods do not fully take advantage of the correlation structure between SNPs and their multimarker proxies. In this article, we propose a novel multimarker indirect-association method, WHAP, that is based on a weighted sum of the haplotype frequency differences. In contrast to traditional indirect-association methods, we show analytically that there is a considerable gain in power achieved by our method compared with both single-marker and multimarker tests, as well as traditional haplotype-based tests. Our results are supported by empirical evaluation across the HapMap reference panel data sets, and a software implementation for the Affymetrix 500k and Illumina HumanHap 550 chips is available for download.

Mesh:

Substances:

Year:  2007        PMID: 17357074      PMCID: PMC1852710          DOI: 10.1086/513109

Source DB:  PubMed          Journal:  Am J Hum Genet        ISSN: 0002-9297            Impact factor:   11.025


  22 in total

1.  Power of linkage versus association analysis of quantitative traits, by use of variance-components models, for sibship data.

Authors:  P C Sham; S S Cherny; S Purcell; J K Hewitt
Journal:  Am J Hum Genet       Date:  2000-04-12       Impact factor: 11.025

2.  Haplotype tagging for the identification of common disease genes.

Authors:  G C Johnson; L Esposito; B J Barratt; A N Smith; J Heward; G Di Genova; H Ueda; H J Cordell; I A Eaves; F Dudbridge; R C Twells; F Payne; W Hughes; S Nutland; H Stevens; P Carr; E Tuomilehto-Wolf; J Tuomilehto; S C Gough; D G Clayton; J A Todd
Journal:  Nat Genet       Date:  2001-10       Impact factor: 38.330

3.  Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium.

Authors:  Christopher S Carlson; Michael A Eberle; Mark J Rieder; Qian Yi; Leonid Kruglyak; Deborah A Nickerson
Journal:  Am J Hum Genet       Date:  2003-12-15       Impact factor: 11.025

4.  Selection and evaluation of tagging SNPs in the neuronal-sodium-channel gene SCN1A: implications for linkage-disequilibrium gene mapping.

Authors:  Mike E Weale; Chantal Depondt; Stuart J Macdonald; Alice Smith; Poh San Lai; Simon D Shorvon; Nicholas W Wood; David B Goldstein
Journal:  Am J Hum Genet       Date:  2003-07-29       Impact factor: 11.025

5.  Detecting disease associations due to linkage disequilibrium using haplotype tags: a class of tests and the determinants of statistical power.

Authors:  Juliet M Chapman; Jason D Cooper; John A Todd; David G Clayton
Journal:  Hum Hered       Date:  2003       Impact factor: 0.444

6.  Testing untyped alleles (TUNA)-applications to genome-wide association studies.

Authors:  Dan L Nicolae
Journal:  Genet Epidemiol       Date:  2006-12       Impact factor: 2.135

7.  A comparison of linkage disequilibrium measures for fine-scale mapping.

Authors:  B Devlin; N Risch
Journal:  Genomics       Date:  1995-09-20       Impact factor: 5.736

Review 8.  Linkage disequilibrium in humans: models and data.

Authors:  J K Pritchard; M Przeworski
Journal:  Am J Hum Genet       Date:  2001-06-14       Impact factor: 11.025

9.  Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population.

Authors:  L Excoffier; M Slatkin
Journal:  Mol Biol Evol       Date:  1995-09       Impact factor: 16.240

10.  Modeling and E-M estimation of haplotype-specific relative risks from genotype data for a case-control study of unrelated individuals.

Authors:  Daniel O Stram; Celeste Leigh Pearce; Phillip Bretsky; Matthew Freedman; Joel N Hirschhorn; David Altshuler; Laurence N Kolonel; Brian E Henderson; Duncan C Thomas
Journal:  Hum Hered       Date:  2003       Impact factor: 0.444

View more
  32 in total

1.  Family-based association tests using genotype data with uncertainty.

Authors:  Zhaoxia Yu
Journal:  Biostatistics       Date:  2011-12-08       Impact factor: 5.899

2.  Fast and robust association tests for untyped SNPs in case-control studies.

Authors:  Andrew S Allen; Glen A Satten; Sarah L Bray; Frank Dudbridge; Michael P Epstein
Journal:  Hum Hered       Date:  2010-07-30       Impact factor: 0.444

3.  A powerful and flexible multilocus association test for quantitative traits.

Authors:  Lydia Coulter Kwee; Dawei Liu; Xihong Lin; Debashis Ghosh; Michael P Epstein
Journal:  Am J Hum Genet       Date:  2008-02       Impact factor: 11.025

4.  Simple and efficient analysis of disease association with missing genotype data.

Authors:  D Y Lin; Y Hu; B E Huang
Journal:  Am J Hum Genet       Date:  2008-02       Impact factor: 11.025

5.  ATOM: a powerful gene-based association test by combining optimally weighted markers.

Authors:  Mingyao Li; Kai Wang; Struan F A Grant; Hakon Hakonarson; Chun Li
Journal:  Bioinformatics       Date:  2008-12-15       Impact factor: 6.937

6.  A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals.

Authors:  Brian L Browning; Sharon R Browning
Journal:  Am J Hum Genet       Date:  2009-02-05       Impact factor: 11.025

7.  Linkage effects and analysis of finite sample errors in the HapMap.

Authors:  Noah Zaitlen; Hyun Min Kang; Eleazar Eskin
Journal:  Hum Hered       Date:  2009-04-09       Impact factor: 0.444

8.  Multimarker analysis and imputation of multiple platform pooling-based genome-wide association studies.

Authors:  Nils Homer; Waibhav D Tembe; Szabolcs Szelinger; Margot Redman; Dietrich A Stephan; John V Pearson; Stanley F Nelson; David Craig
Journal:  Bioinformatics       Date:  2008-07-10       Impact factor: 6.937

9.  An MCMC algorithm for haplotype assembly from whole-genome sequence data.

Authors:  Vikas Bansal; Aaron L Halpern; Nelson Axelrod; Vineet Bafna
Journal:  Genome Res       Date:  2008-08       Impact factor: 9.043

Review 10.  Missing data imputation and haplotype phase inference for genome-wide association studies.

Authors:  Sharon R Browning
Journal:  Hum Genet       Date:  2008-10-11       Impact factor: 4.132

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.