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

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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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References

  • Altshuler D, Daly M (2007) Guilt beyond a reasonable doubt. Nat Genet 39:813–815

    Article  PubMed  CAS  Google Scholar 

  • Anderson CA, Pettersson FH, Barrett JC, Zhuang JJ, Ragoussis J, Cardon LR, Morris AP (2008) Evaluating the effects of imputation on the power, coverage, and cost efficiency of genome-wide SNP platforms. Am J Hum Genet 83:112–119

    Article  PubMed  CAS  Google Scholar 

  • Ayers KL, Sabatti C, Lange K (2007) A dictionary model for haplotyping, genotype calling, and association testing. Genet Epidemiol 31:672–683

    Article  PubMed  Google Scholar 

  • Balding DJ (2006) A tutorial on statistical methods for population association studies. Nat Rev Genet 7:781–791

    Article  PubMed  CAS  Google Scholar 

  • Barrett JC, Hansoul S, Nicolae DL, Cho JH, Duerr RH, Rioux JD, Brant SR, Silverberg MS, Taylor KD, Barmada MM, Bitton A, Dassopoulos T, Datta LW, Green T, Griffiths AM, Kistner EO, Murtha MT, Regueiro MD, Rotter JI, Schumm LP, Steinhart AH, Targan SR, Xavier RJ, Libioulle C, Sandor C, Lathrop M, Belaiche J, Dewit O, Gut I, Heath S, Laukens D, Mni M, Rutgeerts P, Van Gossum A, Zelenika D, Franchimont D, Hugot JP, de Vos M, Vermeire S, Louis E, Cardon LR, Anderson CA, Drummond H, Nimmo E, Ahmad T, Prescott NJ, Onnie CM, Fisher SA, Marchini J, Ghori J, Bumpstead S, Gwilliam R, Tremelling M, Deloukas P, Mansfield J, Jewell D, Satsangi J, Mathew CG, Parkes M, Georges M, Daly MJ (2008) Genome-wide association defines more than 30 distinct susceptibility loci for Crohn’s disease. Nat Genet 40:955–962

    Article  PubMed  CAS  Google Scholar 

  • Browning SR (2006) Multilocus association mapping using variable-length Markov chains. Am J Hum Genet 78:903–913

    Article  PubMed  CAS  Google Scholar 

  • Browning SR (2008) Estimation of pairwise identity by descent from dense genetic marker data in a population sample of haplotypes. Genetics 178:2123–2132

    Article  PubMed  Google Scholar 

  • Browning BL, Browning SR (2007a) Efficient multilocus association mapping for whole genome association studies using localized haplotype clustering. Genet Epidemiol 31:365–375

    Article  PubMed  Google Scholar 

  • Browning SR, Browning BL (2007b) Rapid and accurate haplotype phasing and missing data inference for whole genome association studies by use of localized haplotype clustering. Am J Hum Genet 81:1084–1097

    Article  PubMed  CAS  Google Scholar 

  • Browning BL, Browning SR (2008) Haplotypic analysis of Wellcome Trust Case Control Consortium data. Hum Genet 123:273–280

    Article  PubMed  Google Scholar 

  • Campbell CD, Ogburn EL, Lunetta KL, Lyon HN, Freedman ML, Groop LC, Altshuler D, Ardlie KG, Hirschhorn JN (2005) Demonstrating stratification in a European American population. Nat Genet 37:868–872

    Article  PubMed  CAS  Google Scholar 

  • Carlson CS, Eberle MA, Rieder MJ, Yi Q, Kruglyak L, Nickerson DA (2004) Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium. Am J Hum Genet 74:106–120

    Article  PubMed  CAS  Google Scholar 

  • Chambers JC, Elliott P, Zabaneh D, Zhang W, Li Y, Froguel P, Balding D, Scott J, Kooner JS (2008) Common genetic variation near MC4R is associated with waist circumference and insulin resistance. Nat Genet 40:716–718

    Article  PubMed  CAS  Google Scholar 

  • Chapman JM, Cooper JD, Todd JA, Clayton DG (2003) Detecting disease associations due to linkage disequilibrium using haplotype tags: a class of tests and the determinants of statistical power. Hum Hered 56:18–31

    Article  PubMed  Google Scholar 

  • Diabetes Genetics Initiative (2007) Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316:1331–1336

    Article  Google Scholar 

  • Dudbridge F (2008) Likelihood-based association analysis for nuclear families and unrelated subjects with missing genotype data. Hum Hered 66:87–98

    Article  PubMed  Google Scholar 

  • Eronen L, Geerts F, Toivonen H (2006) HaploRec: efficient and accurate large-scale reconstruction of haplotypes. BMC Bioinform 7:542

    Article  Google Scholar 

  • Excoffier L, Slatkin M (1995) Maximum-likelihood-estimation of molecular haplotype frequencies in a diploid population. Mol Biol Evol 12:921–927

    PubMed  CAS  Google Scholar 

  • Halperin E, Eskin E (2004) Haplotype reconstruction from genotype data using imperfect phylogeny. Bioinformatics 20:1842–1849

    Article  PubMed  CAS  Google Scholar 

  • Hawley ME, Kidd KK (1995) Haplo—a program using the EM algorithm to estimate the frequencies of multisite haplotypes. J Hered 86:409–411

    PubMed  CAS  Google Scholar 

  • Johnson GC, Esposito L, Barratt BJ, Smith AN, Heward J, Di Genova G, Ueda H, Cordell HJ, Eaves IA, Dudbridge F, Twells RC, Payne F, Hughes W, Nutland S, Stevens H, Carr P, Tuomilehto-Wolf E, Tuomilehto J, Gough SC, Clayton DG, Todd JA (2001) Haplotype tagging for the identification of common disease genes. Nat Genet 29:233–237

    Article  PubMed  CAS  Google Scholar 

  • Lango H, Weedon MN (2008) What will whole genome searches for susceptibility genes for common complex disease offer to clinical practice? J Intern Med 263:16–27

    PubMed  CAS  Google Scholar 

  • Leslie S, Donnelly P, McVean G (2008) A statistical method for predicting classical HLA alleles from SNP data. Am J Hum Genet 82:48–56

    Article  PubMed  CAS  Google Scholar 

  • Lettre G, Jackson AU, Gieger C, Schumacher FR, Berndt SI, Sanna S, Eyheramendy S, Voight BF, Butler JL, Guiducci C, Illig T, Hackett R, Heid IM, Jacobs KB, Lyssenko V, Uda M, Boehnke M, Chanock SJ, Groop LC, Hu FB, Isomaa B, Kraft P, Peltonen L, Salomaa V, Schlessinger D, Hunter DJ, Hayes RB, Abecasis GR, Wichmann HE, Mohlke KL, Hirschhorn JN (2008) Identification of ten loci associated with height highlights new biological pathways in human growth. Nat Genet 40:584–591

    Article  PubMed  CAS  Google Scholar 

  • Li N, Stephens M (2003) Modeling linkage disequilibrium and identifying recombination hotspots using single-nucleotide polymorphism data. Genetics 165:2213–2233

    PubMed  CAS  Google Scholar 

  • Li Y, Ding J, Abecasis GR (2006) Mach 1.0: Rapid haplotype reconstruction and missing genotype inference (abstract 2290). Presented at the annual meeting of the American Society of Human Genetics, 9–13 October 2006, New Orleans, Louisiana. Available from http://www.ashg.org/genetics/ashg06s/index.shtml

  • Li Y, Willer CJ, Ding J, Scheet P, Abecasis GR (2007) In silico genotyping for genome-wide association studies (abstract 2071). Presented at the annual meeting of the American Society of Human Genetics, 23–27 October 2007, San Diego, CA. Available from http://www.ashg.org/genetics/ashg07s/index.shtml

  • Lin S, Cutler DJ, Zwick ME, Chakravarti A (2002) Haplotype inference in random population samples. Am J Hum Genet 71:1129–1137

    Article  PubMed  CAS  Google Scholar 

  • Lin DY, Hu Y, Huang BE (2008) Simple and efficient analysis of disease association with missing genotype data. Am J Hum Genet 82:444–452

    Article  PubMed  CAS  Google Scholar 

  • Listgarten J, Brumme Z, Kadie C, Xiaojiang G, Walker B, Carrington M, Goulder P, Heckerman D (2008) Statistical resolution of ambiguous HLA typing data. PLoS Comput Biol 4:e1000016

    Article  PubMed  Google Scholar 

  • Long JC, Williams RC, Urbanek M (1995) An E-M algorithm and testing strategy for multiple-locus haplotypes. Am J Hum Genet 56:799–810

    PubMed  CAS  Google Scholar 

  • Marchini J, Cutler D, Patterson N, Stephens M, Eskin E, Halperin E, Lin S, Qin ZS, Munro HM, Abecasis GR, Donnelly P (2006) A comparison of phasing algorithms for trios and unrelated individuals. Am J Hum Genet 78:437–450

    Article  PubMed  CAS  Google Scholar 

  • Marchini J, Howie B, Myers S, McVean G, Donnelly P (2007) A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet 39:906–913

    Article  PubMed  CAS  Google Scholar 

  • Nicolae DL (2006) Testing untyped alleles (TUNA)-applications to genome-wide association studies. Genet Epidemiol 30:718–727

    Article  PubMed  Google Scholar 

  • Pe’er I, de Bakker PI, Maller J, Yelensky R, Altshuler D, Daly MJ (2006) Evaluating and improving power in whole-genome association studies using fixed marker sets. Nat Genet 38:663–667

    Article  PubMed  CAS  Google Scholar 

  • Qin ZS, Niu T, Liu JS (2002) Partition–ligation–expectation-maximization algorithm for haplotype inference with single-nucleotide polymorphisms. Am J Hum Genet 71:1242–1247

    Article  PubMed  CAS  Google Scholar 

  • Rabiner LR (1989) A tutorial on hidden Markov models and selected applications in speech recognition. Proc IEEE 77:257–286

    Article  Google Scholar 

  • Raelson JV, Little RD, Ruether A, Fournier H, Paquin B, Van Eerdewegh P, Bradley WE, Croteau P, Nguyen-Huu Q, Segal J, Debrus S, Allard R, Rosenstiel P, Franke A, Jacobs G, Nikolaus S, Vidal JM, Szego P, Laplante N, Clark HF, Paulussen RJ, Hooper JW, Keith TP, Belouchi A, Schreiber S (2007) Genome-wide association study for Crohn’s disease in the Quebec Founder Population identifies multiple validated disease loci. Proc Natl Acad Sci USA 104:14747–14752

    Article  PubMed  CAS  Google Scholar 

  • Schaid DJ (2004) Evaluating associations of haplotypes with traits. Genet Epidemiol 27:348–364

    Article  PubMed  Google Scholar 

  • Scheet P, Stephens M (2006) A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase. Am J Hum Genet 78:629–644

    Article  PubMed  CAS  Google Scholar 

  • Scheet P, Stephens M, Abecasis GR (2007) Whole genome linkage disequilibrium association mapping of binary traits (abstract 209). Presented at the annual meeting of the American Society of Human Genetics, 23–27 October 2007, San Diego, CA. Available from http://www.ashg.org/genetics/ashg07s/index.shtml

  • Scott LJ, Mohlke KL, Bonnycastle LL, Willer CJ, Li Y, Duren WL, Erdos MR, Stringham HM, Chines PS, Jackson AU, Prokunina-Olsson L, Ding CJ, Swift AJ, Narisu N, Hu T, Pruim R, Xiao R, Li XY, Conneely KN, Riebow NL, Sprau AG, Tong M, White PP, Hetrick KN, Barnhart MW, Bark CW, Goldstein JL, Watkins L, Xiang F, Saramies J, Buchanan TA, Watanabe RM, Valle TT, Kinnunen L, Abecasis GR, Pugh EW, Doheny KF, Bergman RN, Tuomilehto J, Collins FS, Boehnke M (2007) A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 316:1341–1345

    Article  PubMed  CAS  Google Scholar 

  • Servin B, Stephens M (2007) Imputation-based analysis of association studies: candidate regions and quantitative traits. PLoS Genet 3:e114

    Article  PubMed  Google Scholar 

  • Stephens M, Donnelly P (2003) A comparison of Bayesian methods for haplotype reconstruction from population genotype data. Am J Hum Genet 73:1162–1169

    Article  PubMed  CAS  Google Scholar 

  • Stephens M, Scheet P (2005) Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation. Am J Hum Genet 76:449–462

    Article  PubMed  CAS  Google Scholar 

  • Stephens M, Smith NJ, Donnelly P (2001) A new statistical method for haplotype reconstruction from population data. Am J Hum Genet 68:978–989

    Article  PubMed  CAS  Google Scholar 

  • The International HapMap Consortium (2005) A haplotype map of the human genome. Nature 437:1299–1320

    Article  Google Scholar 

  • The International HapMap Consortium (2007) A second generation human haplotype map of over 3.1 million SNPs. Nature 449:851–861

    Article  Google Scholar 

  • The Wellcome Trust Case Control Consortium (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447:661–678

    Article  Google Scholar 

  • Wang WY, Barratt BJ, Clayton DG, Todd JA (2005) Genome-wide association studies: theoretical and practical concerns. Nat Rev Genet 6:109–118

    Article  PubMed  CAS  Google Scholar 

  • Willer CJ, Sanna S, Jackson AU, Scuteri A, Bonnycastle LL, Clarke R, Heath SC, Timpson NJ, Najjar SS, Stringham HM, Strait J, Duren WL, Maschio A, Busonero F, Mulas A, Albai G, Swift AJ, Morken MA, Narisu N, Bennett D, Parish S, Shen H, Galan P, Meneton P, Hercberg S, Zelenika D, Chen WM, Li Y, Scott LJ, Scheet PA, Sundvall J, Watanabe RM, Nagaraja R, Ebrahim S, Lawlor DA, Ben-Shlomo Y, Davey-Smith G, Shuldiner AR, Collins R, Bergman RN, Uda M, Tuomilehto J, Cao A, Collins FS, Lakatta E, Lathrop GM, Boehnke M, Schlessinger D, Mohlke KL, Abecasis GR (2008) Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nat Genet 40:161–169

    Article  PubMed  CAS  Google Scholar 

  • Yu Z, Schaid DJ (2007) Methods to impute missing genotypes for population data. Hum Genet 122:495–504

    Article  PubMed  Google Scholar 

  • Zaitlen N, Kang HM, Eskin E, Halperin E (2007) Leveraging the HapMap correlation structure in association studies. Am J Hum Genet 80:683–691

    Article  PubMed  CAS  Google Scholar 

  • Zeggini E, Scott LJ, Saxena R, Voight BF, Marchini JL, Hu T, de Bakker PI, Abecasis GR, Almgren P, Andersen G, Ardlie K, Bostrom KB, Bergman RN, Bonnycastle LL, Borch-Johnsen K, Burtt NP, Chen H, Chines PS, Daly MJ, Deodhar P, Ding CJ, Doney AS, Duren WL, Elliott KS, Erdos MR, Frayling TM, Freathy RM, Gianniny L, Grallert H, Grarup N, Groves CJ, Guiducci C, Hansen T, Herder C, Hitman GA, Hughes TE, Isomaa B, Jackson AU, Jorgensen T, Kong A, Kubalanza K, Kuruvilla FG, Kuusisto J, Langenberg C, Lango H, Lauritzen T, Li Y, Lindgren CM, Lyssenko V, Marvelle AF, Meisinger C, Midthjell K, Mohlke KL, Morken MA, Morris AD, Narisu N, Nilsson P, Owen KR, Palmer CN, Payne F, Perry JR, Pettersen E, Platou C, Prokopenko I, Qi L, Qin L, Rayner NW, Rees M, Roix JJ, Sandbaek A, Shields B, Sjogren M, Steinthorsdottir V, Stringham HM, Swift AJ, Thorleifsson G, Thorsteinsdottir U, Timpson NJ, Tuomi T, Tuomilehto J, Walker M, Watanabe RM, Weedon MN, Willer CJ, Illig T, Hveem K, Hu FB, Laakso M, Stefansson K, Pedersen O, Wareham NJ, Barroso I, Hattersley AT, Collins FS, Groop L, McCarthy MI, Boehnke M, Altshuler D (2008) Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet 40:638–645

    Article  PubMed  CAS  Google Scholar 

  • Zeggini E, Weedon MN, Lindgren CM, Frayling TM, Elliott KS, Lango H, Timpson NJ, Perry JR, Rayner NW, Freathy RM, Barrett JC, Shields B, Morris AP, Ellard S, Groves CJ, Harries LW, Marchini JL, Owen KR, Knight B, Cardon LR, Walker M, Hitman GA, Morris AD, Doney AS, McCarthy MI, Hattersley AT (2007) Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science 316:1336–1341

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

The author thanks Brian Browning for helpful discussions and the anonymous reviewers for their comments. This work was supported by NIH grant 3R01GM075091-02S1.

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  1. Department of Statistics, The University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand

    Sharon R. Browning

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Correspondence to Sharon R. Browning.

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Browning, S.R. Missing data imputation and haplotype phase inference for genome-wide association studies. Hum Genet 124, 439–450 (2008). https://doi.org/10.1007/s00439-008-0568-7

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