Single-variant and multi-variant trend tests for genetic association with next-generation sequencing that are robust to sequencing error

Human Heredity

Volumn 74, Issue 3-4, 2012, Pages 172-183

  Kim, Wonkuk ^a   Londono, Douglas ^b   Zhou, Lisheng ^b   Xing, Jinchuan ^b   Nato, Alejandro Q ^b   Musolf, Anthony ^b   Matise, Tara C ^b   Finch, Stephen J ^c   Gordon, Derek ^b  

^a UNIVERSITY OF SOUTH FLORIDA   (United States)

^b Life Sciences Building Rutgers University   (United States)

^c Stony Brook University   (United States)

Author keywords

Allele; Genetic association; GWAS; Locus; Next generation sequencing; Rare variant; Trend test

Indexed keywords

ARTICLE; GENE FREQUENCY; GENE LINKAGE DISEQUILIBRIUM; GENE LOCUS; GENE SEQUENCE; GENETIC ASSOCIATION; GENETIC VARIABILITY; GENOTYPE; HUMAN; NEXT GENERATION SEQUENCING; PHENOTYPE; SINGLE NUCLEOTIDE POLYMORPHISM;

EID: 84876482595     PISSN: 00015652     EISSN: 14230062     Source Type: Journal    
DOI: 10.1159/000346824     Document Type: Article

References (82)

1. Ott J: Analysis of Human Genetic Linkage, 3 ed. Baltimore, Johns Hopkins University Press, 1999.
2. Purcell S, Cherny SS, Sham PC: Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits. Bioinformatics 2003; 19: 149-150.
3. Skol AD, Scott LJ, Abecasis GR, Boehnke M: Joint analysis is more efficient than replication- based analysis for two-stage genomewide association studies. Nat Genet 2006; 38: 209-213.
4. Edwards BJ, Haynes C, Levenstien MA, Finch SJ, Gordon D: Power and sample size calculations in the presence of phenotype errors for case/control genetic association studies. BMC Genet 2005; 6: 18.
5. Lamina C, Kuchenhoff H, Chang-Claude J, Paulweber B, Wichmann HE, Illig T, Hoehe MR, Kronenberg F, Heid IM: Haplotype misclassification resulting from statistical reconstruction and genotype error, and its impact on association estimates. Ann Hum Genet 2010; 74: 452-462.
6. Kennedy J, Mandoiu I, Pasaniuc B: Genotype error detection using Hidden Markov Models of haplotype diversity. J Comput Biol 2008; 15: 1155-1171.
7. Browning BL, Browning SR: Haplotypic analysis of Wellcome Trust Case Control Consortium data. Hum Genet 2008; 123: 273-280.
8. Cheng KF, Lin WJ: Simultaneously correcting for population stratification and for genotyping error in case-control association studies. Am J Hum Genet 2007; 81: 726-743.
9. Cheng KF, Chen JH: A simple and robust TDT-type test against genotyping error with error rates varying across families. Hum Hered 2007; 64: 114-122.
10. Gordon D, Yang Y, Haynes C, Finch SJ, Mendell NR, Brown AM, Haroutunian V: Increasing power for tests of genetic association in the presence of phenotype and/or genotype error by use of double-sampling. Stat Appl Genet Mol Biol 2004; 3:Article26.
11. Moskvina V, Craddock N, Holmans P, Owen MJ, O'Donovan MC: Effects of differential genotyping error rate on the type I error probability of case-control studies. Hum Hered 2006; 61: 55-64.
12. Hao K, Wang X: Incorporating individual error rate into association test of unmatched case-control design. Hum Hered 2004; 58: 154-163.
13. Kang SJ, Gordon D, Brown AM, Ott J, Finch SJ: Tradeoff between no-call reduction in genotyping error rate and loss of sample size for genetic case/control association studies. Pac Symp Biocomput 2004; 116-127.
14. Morris RW, Kaplan NL: Testing for association with a case-parents design in the presence of genotyping errors. Genet Epidemiol 2004; 26: 142-154.
15. Bernardinelli L, Berzuini C, Seaman S, Holmans P: Bayesian trio models for association in the presence of genotyping errors. Genet Epidemiol 2004; 26: 70-80.
16. Barral S, Haynes C, Stone M, Gordon D: LRTae: improving statistical power for genetic association with case/control data when phenotype and/or genotype misclassification errors are present. BMC Genet 2006; 7: 24.
17. Dahabreh IJ, Linardou H, Bouzika P, Varvarigou V, Murray S: TP53 Arg72Pro polymorphism and colorectal cancer risk: a systematic review and meta-analysis. Cancer Epidemiol Biomarkers Prev 2010; 19: 1840-1847.
18. Heid IM, Lamina C, Kuchenhoff H, Fischer G, Klopp N, Kolz M, Grallert H, Vollmert C, Wagner S, Huth C, Muller J, Muller M, Hunt SC, Peters A, Paulweber B, Wichmann HE, Kronenberg F, Illig T: Estimating the single nucleotide polymorphism genotype misclassification from routine double measurements in a large epidemiologic sample. Am J Epidemiol 2008; 168: 878-889.
19. Holmes MV, Perel P, Shah T, Hingorani AD, Casas JP: CYP2C19 genotype, clopidogrel metabolism, platelet function, and cardiovascular events: a systematic review and metaanalysis. JAMA 2011; 306: 2704-2714.
20. Hossain S, Le ND, Brooks-Wilson AR, Spinelli JJ: Impact of genotype misclassification on genetic association estimates and the bayesian adjustment. Am J Epidemiol 2009; 170: 994-1004.
21. Ji F, Yang Y, Haynes C, Finch SJ, Gordon D: Computing asymptotic power and sample size for case-control genetic association studies in the presence of phenotype and/or genotype misclassification errors. Stat Appl Genet Mol Biol 2005; 4:Article37.
22. Lai R, Zhang H, Yang Y: Repeated measurement sampling in genetic association analysis with genotyping errors. Genet Epidemiol 2007; 31: 143-153.
23. Li J, Coates RJ, Gwinn M, Khoury MJ: Steroid 5-{alpha}-reductase Type 2 (SRD5a2) gene polymorphisms and risk of prostate cancer: a HuGE review. Am J Epidemiol 2010; 171: 1-13.
24. Kang SJ, Finch SJ, Haynes C, Gordon D: Quantifying the percent increase in minimum sample size for SNP genotyping errors in genetic model-based association studies. Hum Hered 2004; 58: 139-144.
25. Kang SJ, Gordon D, Finch SJ: What SNP genotyping errors are most costly for genetic association studies? Genet Epidemiol 2004; 26: 132-141.
26. Ahn K, Gordon D, Finch SJ: Increase of rejection rate in case-control studies with the differential genotyping error rates. Stat Appl Genet Mol Biol 2009; 8:Article25.
27. Ahn K, Haynes C, Kim W, Fleur RS, Gordon D, Finch SJ: The effects of SNP genotyping errors on the power of the Cochran-Armitage linear trend test for case/control association studies. Ann Hum Genet 2007; 71: 249-261.
28. Gordon D, Haynes C, Blumenfeld J, Finch SJ: PAWE-3D: visualizing power for association with error in case-control genetic studies of complex traits. Bioinformatics 2005; 21: 3935-3937.
29. Marquard V, Beckmann L, Heid IM, Lamina C, Chang-Claude J: Impact of genotyping errors on the type I error rate and the power of haplotype-based association methods. BMC Genet 2009; 10: 3.
30. Londono D, Haynes C, De La Vega FM, Finch SJ, Gordon D: A cost-effective statistical method to correct for differential genotype misclassification when performing case-control genetic association. Hum Hered 2010; 70: 102-108.
31. Yang Y, Wise CA, Gordon D, Finch SJ: A family- based likelihood ratio test for general pedigree structures that allows for genotyping error and missing data. Hum Hered 2008; 66: 99-110.
32. Gordon D, Haynes C, Yang Y, Kramer PL, Finch SJ: Linear trend tests for case-control genetic association that incorporate random phenotype and genotype misclassification error. Genet Epidemiol 2007; 31: 853-870.
33. Maraganore DM, de Andrade M, Elbaz A, Farrer MJ, Ioannidis JP, Kruger R, Rocca WA, Schneider NK, Lesnick TG, Lincoln SJ, Hulihan MM, Aasly JO, Ashizawa T, Chartier- Harlin MC, Checkoway H, Ferrarese C, Hadjigeorgiou G, Hattori N, Kawakami H, Lambert JC, Lynch T, Mellick GD, Papapetropoulos S, Parsian A, Quattrone A, Riess O, Tan EK, Van Broeckhoven C: Collaborative analysis of alpha-synuclein gene promoter variability and Parkinson disease. JAMA 2006; 296: 661-670.
34. Govindarajulu US, Spiegelman D, Miller KL, Kraft P: Quantifying bias due to allele misclassification in case-control studies of haplotypes. Genet Epidemiol 2006; 30: 590-601.
35. Mitchell AA, Cutler DJ, Chakravarti A: Undetected genotyping errors cause apparent overtransmission of common alleles in the transmission/disequilibrium test. Am J Hum Genet 2003; 72: 598-610.
36. Plagnol V, Cooper JD, Todd JA, Clayton DG: A method to address differential bias in genotyping in large-scale association studies. PLoS Genet 2007; 3:e74.
37. Powers S, Gopalakrishnan S, Tintle N: Assessing the impact of non-differential genotyping errors on rare variant tests of association. Hum Hered 2011; 72: 153-160.
38. Sastre L: New DNA sequencing technologies open a promising era for cancer research and treatment. Clin Transl Oncol 2011; 13: 301-306.
39. Lindblom A, Robinson PN: Bioinformatics for human genetics: promises and challenges. Hum Mutat 2011; 32: 495-500.
40. Patrinos GP, Innocenti F, Cox N, Fortina P: Genetic Analysis in Translational Medicine: The 2010 GOLDEN HELIX Symposium. Hum Mutat 2011; 32: 698-703.
41. Schweiger MR, Kerick M, Timmermann B, Isau M: The power of NGS technologies to delineate the genome organization in cancer: from mutations to structural variations and epigenetic alterations. Cancer Metastasis Rev 2011; 30: 199-210.
42. Cloonan N, Waddell N, Grimmond SM: The clinical potential and challenges of sequencing cancer genomes for personalized medical genomics. IDrugs 2010; 13: 778-781.
43. Weksberg R: Imprinted genes and human disease. Am J Med Genet (Part C) 2010; 154C: 317-320.
44. Kabesch M: Next generation genetics in allergy. Curr Opin Allergy Clin Immunol 2010; 10: 407.
45. Roukos DH: Next-generation, genome sequencing- based biomarkers: concerns and challenges for medical practice. Biomark Med 2010; 4: 583-586.
46. Chen JM, Ferec C, Cooper DN: Revealing the human mutome. Clinical Genet 2010; 78: 310-320.
47. Ku CS, Loy EY, Salim A, Pawitan Y, Chia KS: The discovery of human genetic variations and their use as disease markers: past, present and future. J Hum Genet 2010; 55: 403-415.
48. Dias-Neto E, Nunes DN, Giordano RJ, Sun J, Botz GH, Yang K, Setubal JC, Pasqualini R, Arap W: Next-generation phage display: integrating and comparing available molecular tools to enable cost-effective high-throughput analysis. PloS One 2009; 4:e8338.
49. ten Bosch JR, Grody WW: Keeping up with the next generation: massively parallel sequencing in clinical diagnostics. J Mol Diagn 2008; 10: 484-492.
50. Ng SB, Buckingham KJ, Lee C, Bigham AW, Tabor HK, Dent KM, Huff CD, Shannon PT, Jabs EW, Nickerson DA, Shendure J, Bamshad MJ: Exome sequencing identifies the cause of a mendelian disorder. Nat Genet 2010; 42: 30-35.
51. Ng SB, Bigham AW, Buckingham KJ, Hannibal MC, McMillin MJ, Gildersleeve HI, Beck AE, Tabor HK, Cooper GM, Mefford HC, Lee C, Turner EH, Smith JD, Rieder MJ, Yoshiura K, Matsumoto N, Ohta T, Niikawa N, Nickerson DA, Bamshad MJ, Shendure J: Exome sequencing identifies MLL2 mutations as a cause of Kabuki syndrome. Nat Genet 2010; 42: 790-793.
52. Nyholt DR: A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other. Am J Hum Genet 2004; 74: 765-769.
53. de Bakker PIW, Yelensky R, Pe'er I, Gabriel SB, Daly MJ, Altshuler D: Efficiency and power in genetic association studies. Nat Genet 2005; 37: 1217-1223.
54. Storey JD, Tibshirani R: Statistical significance for genomewide studies. Proc Natl Acad Sci USA 2003; 100: 9440-9445.
55. Ott J, Liu Z, Shen Y: Challenging false discovery rate: a partition test based on p values in human case-control association studies. Hum Hered 2012; 74: 45-50.
56. Chen Z, Liu Q, McGee M, Kong M, Huang X, Deng Y, Scheuermann RH: A gene selection method for GeneChip array data with small sample sizes. BMC Genomics 2011; 12(suppl 5):S7.
57. Muller BU, Stich B, Piepho HP: A general method for controlling the genome-wide type I error rate in linkage and association mapping experiments in plants. Heredity (Edinburgh) 2011; 106: 825-831.
58. Hoh J, Ott J: Scan statistics to scan markers for susceptibility genes. Proc Natl Acad Sci USA 2000; 97: 9615-9617.
59. Hoh J, Ott J: A train of thoughts on gene mapping. Theor Popul Biol 2001; 60: 149-153.
60. Hoh J, Ott J: Mathematical multi-locus approaches to localizing complex human trait genes. Nat Rev Genet 2003; 4: 701-709.
61. Hoh J, Ott J: Genetic dissection of diseases: design and methods. Curr Opin Genet Dev 2004; 14: 229-232.
62. Hoh J, Wille A, Ott J: Trimming, weighting, and grouping SNPs in human case-control association studies. Genome Res 2001; 11: 2115-2119.
63. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC: PLINK: a tool set for whole-genome association and population- based linkage analyses. Am J Hum Genet 2007; 81: 559-575.
64. Zhou H, Pan W: Binomial mixture modelbased association tests under genetic heterogeneity. Ann Hum Genet 2009; 73: 614-630.
65. Cochran WG: Some methods for strengthening the common χ 2 tests. Biometrics 1954; 10: 417-451.
66. Armitage P: Tests for linear trends in proportions and frequencies. Biometrics 1955; 11: 375-386.
67. Kinnamon DD, Hershberger RE, Martin ER: Reconsidering association testing methods using single-variant test statistics as alternatives to pooling tests for sequence data with rare variants. PLoS One 2012; 7:e30238.
68. Schaid DJ, Sommer SS: Genotype relative risks: methods for design and analysis of candidate- gene association studies. Am J Hum Genet 1993; 53: 1114-1126.
69. Zawistowski M, Gopalakrishnan S, Ding J, Li Y, Grimm S, Zollner S: Extending rare-variant testing strategies: analysis of noncoding sequence and imputed genotypes. Am J Hum Genet 2010; 87: 604-617.
70. Wu Michael C, Lee S, Cai T, Li Y, Boehnke M, Lin X: Rare-variant association testing for sequencing data with the sequence kernel association test. Am J Hum Genet 2011; 89: 82-93.
71. - 1000 Genomes Project, Phase 1, Version 3, 2012.
72. - 1000 Genome Project, Exome Alignment File, 2012.
73. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R: The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009; 25: 2078-2079.
74. Ensemble Human Genome Build 37 - Chromosome 20, 2012.
75. Tukey JW: Exploratory Data Analysis. Upper Saddle River, Pearson Education - Addison Wesley, 1977.
76. Pluzhnikov A, Below JE, Konkashbaev A, Tikhomirov A, Kistner-Griffin E, Roe CA, Nicolae DL, Cox NJ: Spoiling the whole bunch: quality control aimed at preserving the integrity of high-throughput genotyping. Am J Hum Genet 2010; 87: 123-128.
77. Cheng KF, Lin WJ: The effects of misclassification in studies of gene-environment interactions. Hum Hered 2009; 67: 77-87.
78. Clayton DG, Walker NM, Smyth DJ, Pask R, Cooper JD, Maier LM, Smink LJ, Lam AC, Ovington NR, Stevens HE, Nutland S, Howson JM, Faham M, Moorhead M, Jones HB, Falkowski M, Hardenbol P, Willis TD, Todd JA: Population structure, differential bias and genomic control in a large-scale, case-control association study. Nat Genet 2005; 37: 1243-1246.
79. Slager SL, Schaid DJ: Case-control studies of genetic markers: power and sample size approximations for Armitage's test for trend. Hum Hered 2001; 52: 149-153.
80. R Development Core Team (2012). R: A Language and Environment for Statistical Computing. Vienna, R Foundation for Statistical Computing. ISBN 3-900051-07-0. http://www.R-project.org/.
81. Anderson CA, Pettersson FH, Clarke GM, Cardon LR, Morris AP, Zondervan KT: Data quality control in genetic case-control association studies. Nat Protoc 2010; 5: 1564-1573.
82. Tenenbein A: A double sampling scheme for estimating from misclassified multinomial data with applications to sampling inspection. Technometrics 1972; 14: 187-202.