Literature DB >> 18850115

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

Sharon R Browning1.   

Abstract

Imputation of missing data and the use of haplotype-based association tests can improve the power of genome-wide association studies (GWAS). In this article, I review methods for haplotype inference and missing data imputation, and discuss their application to GWAS. I discuss common features of the best algorithms for haplotype phase inference and missing data imputation in large-scale data sets, as well as some important differences between classes of methods, and highlight the methods that provide the highest accuracy and fastest computational performance.

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Year:  2008        PMID: 18850115      PMCID: PMC2731769          DOI: 10.1007/s00439-008-0568-7

Source DB:  PubMed          Journal:  Hum Genet        ISSN: 0340-6717            Impact factor:   4.132


  51 in total

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Journal:  Nat Genet       Date:  2005-07-24       Impact factor: 38.330

2.  Multilocus association mapping using variable-length Markov chains.

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3.  Evaluating and improving power in whole-genome association studies using fixed marker sets.

Authors:  Itsik Pe'er; Paul I W de Bakker; Julian Maller; Roman Yelensky; David Altshuler; Mark J Daly
Journal:  Nat Genet       Date:  2006-05-21       Impact factor: 38.330

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

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

5.  Leveraging the HapMap correlation structure in association studies.

Authors:  Noah Zaitlen; Hyun Min Kang; Eleazar Eskin; Eran Halperin
Journal:  Am J Hum Genet       Date:  2007-03-02       Impact factor: 11.025

6.  A comparison of phasing algorithms for trios and unrelated individuals.

Authors:  Jonathan Marchini; David Cutler; Nick Patterson; Matthew Stephens; Eleazar Eskin; Eran Halperin; Shin Lin; Zhaohui S Qin; Heather M Munro; Goncalo R Abecasis; Peter Donnelly
Journal:  Am J Hum Genet       Date:  2006-01-26       Impact factor: 11.025

7.  A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase.

Authors:  Paul Scheet; Matthew Stephens
Journal:  Am J Hum Genet       Date:  2006-02-17       Impact factor: 11.025

8.  Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease.

Authors:  Jeffrey C Barrett; Sarah Hansoul; Dan L Nicolae; Judy H Cho; Richard H Duerr; John D Rioux; Steven R Brant; Mark S Silverberg; Kent D Taylor; M Michael Barmada; Alain Bitton; Themistocles Dassopoulos; Lisa Wu Datta; Todd Green; Anne M Griffiths; Emily O Kistner; Michael T Murtha; Miguel D Regueiro; Jerome I Rotter; L Philip Schumm; A Hillary Steinhart; Stephan R Targan; Ramnik J Xavier; Cécile Libioulle; Cynthia Sandor; Mark Lathrop; Jacques Belaiche; Olivier Dewit; Ivo Gut; Simon Heath; Debby Laukens; Myriam Mni; Paul Rutgeerts; André Van Gossum; Diana Zelenika; Denis Franchimont; Jean-Pierre Hugot; Martine de Vos; Severine Vermeire; Edouard Louis; Lon R Cardon; Carl A Anderson; Hazel Drummond; Elaine Nimmo; Tariq Ahmad; Natalie J Prescott; Clive M Onnie; Sheila A Fisher; Jonathan Marchini; Jilur Ghori; Suzannah Bumpstead; Rhian Gwilliam; Mark Tremelling; Panos Deloukas; John Mansfield; Derek Jewell; Jack Satsangi; Christopher G Mathew; Miles Parkes; Michel Georges; Mark J Daly
Journal:  Nat Genet       Date:  2008-06-29       Impact factor: 38.330

Review 9.  A tutorial on statistical methods for population association studies.

Authors:  David J Balding
Journal:  Nat Rev Genet       Date:  2006-10       Impact factor: 53.242

10.  HaploRec: efficient and accurate large-scale reconstruction of haplotypes.

Authors:  Lauri Eronen; Floris Geerts; Hannu Toivonen
Journal:  BMC Bioinformatics       Date:  2006-12-22       Impact factor: 3.169

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  75 in total

1.  The effect of reference panels and software tools on genotype imputation.

Authors:  Kwangsik Nho; Li Shen; Sungeun Kim; Shanker Swaminathan; Shannon L Risacher; Andrew J Saykin
Journal:  AMIA Annu Symp Proc       Date:  2011-10-22

2.  Performance of genotype imputations using data from the 1000 Genomes Project.

Authors:  Yun Ju Sung; Lihua Wang; Tuomo Rankinen; Claude Bouchard; D C Rao
Journal:  Hum Hered       Date:  2011-12-30       Impact factor: 0.444

3.  Mapping rare and common causal alleles for complex human diseases.

Authors:  Soumya Raychaudhuri
Journal:  Cell       Date:  2011-09-30       Impact factor: 41.582

4.  Effects of missing marker and segregation distortion on QTL mapping in F2 populations.

Authors:  Luyan Zhang; Shiquan Wang; Huihui Li; Qiming Deng; Aiping Zheng; Shuangcheng Li; Ping Li; Zhonglai Li; Jiankang Wang
Journal:  Theor Appl Genet       Date:  2010-06-10       Impact factor: 5.699

Review 5.  Genotype imputation for genome-wide association studies.

Authors:  Jonathan Marchini; Bryan Howie
Journal:  Nat Rev Genet       Date:  2010-07       Impact factor: 53.242

6.  Bayesian epistasis association mapping via SNP imputation.

Authors:  Yu Zhang
Journal:  Biostatistics       Date:  2010-10-05       Impact factor: 5.899

7.  Practical Consideration of Genotype Imputation: Sample Size, Window Size, Reference Choice, and Untyped Rate.

Authors:  Boshao Zhang; Degui Zhi; Kui Zhang; Guimin Gao; Nita N Limdi; Nianjun Liu
Journal:  Stat Interface       Date:  2011       Impact factor: 0.582

8.  A comprehensive evaluation of SNP genotype imputation.

Authors:  Michael Nothnagel; David Ellinghaus; Stefan Schreiber; Michael Krawczak; Andre Franke
Journal:  Hum Genet       Date:  2008-12-17       Impact factor: 4.132

9.  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

Review 10.  Validating, augmenting and refining genome-wide association signals.

Authors:  John P A Ioannidis; Gilles Thomas; Mark J Daly
Journal:  Nat Rev Genet       Date:  2009-05       Impact factor: 53.242

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