Literature DB >> 15543638

Evaluating associations of haplotypes with traits.

Daniel J Schaid1.   

Abstract

Haplotypes have played a major role in the study of highly-penetrant single-gene disorders, and recent evidence that the human genome has hot-spots and cold-spots for recombination have suggested that haplotype-based methods may play a key role in the study of common complex traits. This report reviews the motivation of using haplotypes for the study of the genetic basis of human traits, ranging from biologic function, to statistical power advantages of haplotypes, to linkage disequilibrium fine-mapping. Recent developments of regression models for haplotype analyses are reviewed, offering a synthesis of current methods, as well as their limitations and areas that require further research. Regression models provide significant advantages, such as the ability to control for non-genetic covariates, the effects of the haplotypes can be modeled, step-wise selection can be used to screen for a subset of markers that explain most of the association, haplotype x environment interactions can be evaluated, and regression diagnostics are well developed. Despite these strengths, the current regression methods tend to lack the sophisticated population genetic perspectives offered by coalescent and other similar approaches. Future work that links regression methods with population genetic models may prove beneficial.

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Year:  2004        PMID: 15543638     DOI: 10.1002/gepi.20037

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  135 in total

1.  Power of single- vs. multi-marker tests of association.

Authors:  Xuefeng Wang; Nathan J Morris; Daniel J Schaid; Robert C Elston
Journal:  Genet Epidemiol       Date:  2012-05-30       Impact factor: 2.135

2.  Structures and Assumptions: Strategies to Harness Gene × Gene and Gene × Environment Interactions in GWAS.

Authors:  Charles Kooperberg; Michael Leblanc; James Y Dai; Indika Rajapakse
Journal:  Stat Sci       Date:  2009       Impact factor: 2.901

3.  A sparse marker extension tree algorithm for selecting the best set of haplotype tagging single nucleotide polymorphisms.

Authors:  Ke Hao; Simin Liu; Tianhua Niu
Journal:  Genet Epidemiol       Date:  2005-12       Impact factor: 2.135

4.  Theoretical basis for the identification of allelic variants that encode drug efficacy and toxicity.

Authors:  Min Lin; Rongling Wu
Journal:  Genetics       Date:  2005-03-31       Impact factor: 4.562

5.  Regression-based association analysis with clustered haplotypes through use of genotypes.

Authors:  Jung-Ying Tzeng; Chih-Hao Wang; Jau-Tsuen Kao; Chuhsing Kate Hsiao
Journal:  Am J Hum Genet       Date:  2005-12-19       Impact factor: 11.025

6.  Extended IL10 haplotypes and their association with HIV progression to AIDS.

Authors:  T K Oleksyk; S Shrestha; A L Truelove; J J Goedert; S M Donfield; J Phair; S Mehta; S J O'Brien; M W Smith
Journal:  Genes Immun       Date:  2009-03-19       Impact factor: 2.676

7.  Risk haplotype analysis for bovine paratuberculosis.

Authors:  Pablo J Pinedo; Chenguang Wang; Yao Li; D Owen Rae; Rongling Wu
Journal:  Mamm Genome       Date:  2009-01-15       Impact factor: 2.957

8.  Power comparisons between similarity-based multilocus association methods, logistic regression, and score tests for haplotypes.

Authors:  Wan-Yu Lin; Daniel J Schaid
Journal:  Genet Epidemiol       Date:  2009-04       Impact factor: 2.135

9.  VKORC1 polymorphisms, haplotypes and haplotype groups on warfarin dose among African-Americans and European-Americans.

Authors:  Nita A Limdi; T Mark Beasley; Michael R Crowley; Joyce A Goldstein; Mark J Rieder; David A Flockhart; Donna K Arnett; Ronald T Acton; Nianjun Liu
Journal:  Pharmacogenomics       Date:  2008-10       Impact factor: 2.533

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

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