Curve-based multivariate distance matrix regression analysis: Application to genetic association analyses involving repeated measures

Physiological Genomics

Volumn 42, Issue 2, 2010, Pages 236-247

  Salem, Rany M ^a,b,c,d   O'Connor, Daniel T ^c   Schork, Nicholas J ^c,d  

^a BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^b BOSTON CHILDREN S HOSPITAL   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d SCRIPPS RESEARCH INSTITUTE   (United States)

Author keywords

Longitudinal profiles; Similarity analysis

Indexed keywords

TYRAMINE;

ARTICLE; BLOOD VESSEL; CLINICAL STUDY; COST; CURVE BASED MULTIVARIATE DISTANCE MATRIX REGRESSION; DATA ANALYSIS; GENE EXPRESSION; GENETIC ASSOCIATION; GENOTYPE; HUMAN; HUMAN GENOME PROJECT; HYPOTHESIS; INFORMATION PROCESSING; MULTIVARIATE LOGISTIC REGRESSION ANALYSIS; PHENOTYPE; PRIORITY JOURNAL; SIMULATION; STANDARD; HUMAN GENOME; METABOLISM; REGRESSION ANALYSIS;

GENOME, HUMAN; GENOME-WIDE ASSOCIATION STUDY; HUMANS; PHENOTYPE; REGRESSION ANALYSIS; TYRAMINE;

EID: 77955459668     PISSN: 10948341     EISSN: 15312267     Source Type: Journal    
DOI: 10.1152/physiolgenomics.00118.2009     Document Type: Article

References (98)

1. Anderson MJ. A new method for non-parametric multivariate analysis of variance. Austral Ecol 26: 32-46, 2001.
2. Anderson MJ, Robinson J. Permutation tests for linear models. Austral NZ J Stat 43: 75-88, 2001.
3. Beaty TH, Khoury MJ. Interface of genetics and epidemiology. Epidemiol Rev 22: 120-125, 2000.
4. Behseta S, Kass RE. Testing equality of two functions using BARS. Stat Med 24: 3523-3534, 2005.
5. Bell PA, Chaturvedi S, Gelfand CA, Huang CY, Kochersperger M, Kopla R, Modica F, Pohl M, Varde S, Zhao R, Zhao X, Boyce-Jacino MT, Yassen A. SNPstream UHT: ultra-high throughput SNP genotyping for pharmacogenomics and drug discovery. Biotechniques Suppl: 70-72, 74, 76-77, 2002.
6. Belmont JW, Leal SM. Complex phenotypes and complex genetics: an introduction to genetic studies of complex traits. Curr Atheroscler Rep 7: 180-187, 2005. (Pubitemid 40796749)
7. Burton P, Gurrin L, Sly P. Extending the simple linear regression model to account for correlated responses: an introduction to generalized estimating equations and multi-level mixed modelling. Stat Med 17: 1261-1291, 1998.
8. Chakravarti A, Little P. Nature, nurture and human disease. Nature 421: 412-414, 2003.
9. Collins FS. The case for a US prospective cohort study of genes and environment. Nature 429: 475-477, 2004.
10. Collins FS, Green ED, Guttmacher AE, Guyer MS. A vision for the future of genomics research. Nature 422: 835-847, 2003.
11. Daniels MJ, Zhao YD. Modelling the random effects covariance matrix in longitudinal data. Stat Med 22: 1631-1647, 2003.
12. Denison DGT, Mallick BK, Smith AFM. Automatic Bayesian curve fitting. J Roy Stat Soc Ser B 60: 333-350, 1998.
13. Diggle P. Analysis of Longitudinal Data. New York: Oxford University Press, 2002.
14. Dimatteo I, Genovese CR, Kass RE. Bayesian curve-fitting with freeknot splines. Biometrika 88: 1055-1071, 2001.
15. Durban M, Harezlak J, Wand MP, Carroll RJ. Simple fitting of subject-specific curves for longitudinal data. Stat Med 24: 1153-1167, 2005. (Pubitemid 40485755)
16. Edgington ES. Randomization Tests. New York: M. Dekker, 1995.
17. Edwards LJ. Modern statistical techniques for the analysis of longitudinal data in biomedical research. Pediatr Pulmonol 30: 330-344, 2000.
18. Efromovich S. Nonparametric Curve Estimation: Methods, Theory and Applications. New York: Springer, 1999.
19. Engels JM, Diehr P. Imputation of missing longitudinal data: a comparison of methods. J Clin Epidemiol 56: 968-976, 2003.
20. Fan J, Lin SK. Test of significance when data are curves. J Am Stat Assoc 93: 1007-1021, 1998. (Pubitemid 128136901)
21. Fan JB, Oliphant A, Shen R, Kermani BG, Garcia F, Gunderson KL, Hansen M, Steemers F, Butler SL, Deloukas P, Galver L, Hunt S, McBride C, Bibikova M, Rubano T, Chen J, Wickham E, Doucet D, Chang W, Campbell D, Zhang B, Kruglyak S, Bentley D, Haas J, Rigault P, Zhou L, Stuelpnagel J, Chee MS. Highly parallel SNP genotyping. Cold Spring Harb Symp Quant Biol 68: 69-78, 2003.
22. Fung MM, Nguyen C, Mehtani P, Salem RM, Perez B, Thomas B, Das M, Schork NJ, Mahata SK, Ziegler MG, O'Connor DT. Genetic variation within adrenergic pathways determines in vivo effects of presynaptic stimulation in humans. Circulation 117: 517-525, 2008.
23. Gasser T, Kneip A, Kohler W. A flexible and fast method for automatic smoothing. J Am Stat Assoc 86: 643-652, 1991.
24. Gauderman WJ, Macgregor S, Briollais L, Scurrah K, Tobin M, Park T, Wang D, Rao S, John S, Bull S. Longitudinal data analysis in pedigree studies. Genet Epidemiol 25: S18-S28, 2003.
25. Glazier AM, Nadeau JH, Aitman TJ. Finding genes that underlie complex traits. Science 298: 2345-2349, 2002.
26. Goldstein DB. Common genetic variation and human traits. N Engl J Med 360: 1696-1698, 2009.
27. Good PI. Permutation Tests: A Practical Guide to Resampling Methods for Testing Hypotheses. New York: Springer, 2000.
28. Gower JC. Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika 53: 325-338, 1966.
29. Hardin JW, Hilbe J. Generalized Estimating Equations. Boca Raton, FL: Chapman & Hall/CRC, 2003.
30. Hindorff LA, Junkins HA, Mehta JP, Manolio TA. A Catalog of Published Genome-Wide Association Studies. Available at: http://www. genome.gov/ gwastudies. Accessed May 15, 2009.
31. Hirschhorn JN, Daly MJ. Genome-wide association studies for common diseases and complex traits. Nat Rev Genet 6: 95-108, 2005. (Pubitemid 40179532)
32. Hogan JW, Roy J, Korkontzelou C. Handling drop-out in longitudinal studies. Stat Med 23: 1455-1497, 2004.
33. Hou W, Garvan CW, Zhao W, Behnke M, Eyler FD, Wu R. A general model for detecting genetic determinants underlying longitudinal traits with unequally spaced measurements and nonstationary covariance structure. Biostatistics 6: 420-433, 2005.
34. Hughes T, Hyun Y, Liberles DA. Visualising very large phylogenetic trees in three dimensional hyperbolic space. BMC Bioinformatics 5: 48, 2004. (Pubitemid 38751288)
35. Ibrahim JG, Chen MH, Lipsitz SR. Monte Carlo EM for missing covariates in parametric regression models. Biometrics 55: 591-596, 1999.
36. International HapMap Consortium. A haplotype map of the human genome. Nature 437: 1299-1320, 2005.
37. International Human Genome Sequencing Consortium. Initial sequencing and analysis of the human genome. Nature 409: 860-921, 2001.
38. Jockel KH. Finite sample properties and asymptotic efficiency of Monte Carlo tests. Ann Stat 14: 336-347, 1986.
39. Kenward MG, Molenberghs G. Parametric models for incomplete continuous and categorical longitudinal data. Stat Meth Med Res 8: 51-83, 1999.
40. Kibbey C, Calvet A. Molecular Property eXplorer: a novel approach to visualizing SAR using tree-maps and heatmaps. J Chem Inf Model 45: 523-532, 2005.
41. Krzanowski WJ. Note: a comparison of some distance measures applicable to multinomial data, using a rotational fit technique. Biometrics 27: 1062-1068, 1971.
42. Lander ES, Schork NJ. Genetic dissection of complex traits. Science 265: 2037-2048, 1994.
43. Legendre P, Legendre L. Numerical Ecology. Amsterdam: Elsevier, 1998.
44. Li N, Das K, Wu R. Functional mapping of human growth trajectories. J Theor Biol 261: 33-42, 2009.
45. Li Q, Wacholder S, Hunter DJ, Hoover RN, Chanock S, Thomas G, Yu K. Genetic background comparison using distance-based regression, with applications in population stratification evaluation and adjustment. Genet Epidemiol 33: 432-441, 2009.
46. Lin WY, Schaid DJ. Power comparisons between similarity-based multilocus association methods, logistic regression, and score tests for haplotypes. Genet Epidemiol 33: 183-197, 2009.
47. Littell RC, Milliken GA, Stroup WW, Wolfinger RD, Schabenberger O. SAS for Mixed Models. Cary, NC: SAS Institute, 2006.
48. Littell RC, Pendergast J, Natarajan R. Modelling covariance structure in the analysis of repeated measures data. Stat Med 19: 1793-1819, 2000. (Pubitemid 30436064)
49. Little RJA. Modeling the drop-out mechanism in repeated-measures studies. J Am Stat Assoc 90: 1112-1121, 1995.
50. Livak KJ. Allelic discrimination using fluorogenic probes and the 5′ nuclease assay. Genet Anal 14: 143-149, 1999.
51. Ma CX, Casella G, Wu R. Functional mapping of quantitative trait loci underlying the character process: a theoretical framework. Genetics 161: 1751-1762, 2002.
52. Ma CX, Wu R, Casella G. FunMap: functional mapping of complex traits. Bioinformatics 20: 1808-1811, 2004.
53. Mallinckrodt CH, Sanger TM, Dube S, DeBrota DJ, Molenberghs G, Carroll RJ, Potter WZ, Tollefson GD. Assessing and interpreting treatment effects in longitudinal clinical trials with missing data. Biol Psychiatry 53: 754-760, 2003.
54. Mallinckrodt CH, Watkin JG, Molenberghs G, Carroll RJ. Choice of the primary analysis in longitudinal clinical trials. Pharm Stat 3: 161-169, 2004. (Pubitemid 39654837)
55. Manly BFJ. Randomization, Bootstrap, and Monte Carlo Methods in Biology. Boca Raton, FL: Chapman & Hall/ CRC, 1997.
56. Manolio T, Brooks L, Collins F. A HapMap harvest of insights into the genetics of common disease. J Clin Invest 118: 1590-1605, 2008.
57. Manolio TA. Cohort studies and the genetics of complex disease. Nat Genet 41: 5-6, 2009.
58. Manolio TA, Bailey-Wilson JE, Collins FS. Genes, environment and the value of prospective cohort studies. Nat Rev Genet 7: 812-820, 2006. (Pubitemid 44413225)
59. Matsuzaki H, Dong S, Loi H, Di X, Liu G, Hubbell E, Law J, Berntsen T, Chadha M, Hui H, Yang G, Kennedy GC, Webster TA, Cawley S, Walsh PS, Jones KW, Fodor SP, Mei R. Genotyping over 100,000 SNPs on a pair of oligonucleotide arrays. Nat Meth 1: 109-111, 2004.
60. McArdle BH, Anderson MJ. Fitting multivariate models to community data: a comment on distance-based redundancy analysis. Ecology 82: 290-297, 2001.
61. Mein CA, Barratt BJ, Dunn MG, Siegmund T, Smith AN, Esposito L, Nutland S, Stevens HE, Wilson AJ, Phillips MS, Jarvis N, Law S, de Arruda M, Todd JA. Evaluation of single nucleotide polymorphism typing with invader on PCR amplicons and its automation. Genome Res 10: 330-343, 2000.
62. Molenberghs G, Thijs H, Jansen I, Beunckens C, Kenward MG, Mallinckrodt C, Carroll RJ. Analyzing incomplete longitudinal clinical trial data. Biostatistics 5: 445-464, 2004.
63. Nievergelt CM, Libiger O, Schork NJ. Generalized analysis of molecular variance. PLOS Genet 3: e51, 467-478, 2007.
64. Nueda M, Sebastian P, Tarazona S, Garcia-Garcia F, Dopazo J, Ferrer A, Conesa A. Functional assessment of time course microarray data. BMC Bioinformatics 10: S9, 2009.
65. Pearson TA, Manolio TA. How to interpret a genome-wide association study. JAMA 299: 1335-1344, 2008.
66. Pinheiro JC, Bates DM. Mixed-effects Models in S and S-PLUS. New York: Springer, 2000.
67. Ramsay JO, Silverman BW. Functional Data Analysis. New York: Springer, 2005.
68. Rothman KJ, Greenland S. Modern Epidemiology. Philadelphia, PA: Lippincott-Raven, 1998.
69. Schneiderman ED, Willis SM, Kowalski CJ. Clustering on the basis of longitudinal data. Comput Biol Med 23: 399-406, 1993.
70. Schork NJ, Wessel J, Malo N. DNA sequence-based phenotypic association analysis. In: Genetic Dissection of Complex Traits (vol. 60, 2nd ed.), edited by Rao DC, Gu CC: Academic Press, 2008, p. 195-217.
71. Schucany WR. Kernel smoothers: an overview of curve estimators for the first graduate course in nonparametric statistics. Stat Sci 19: 663-675, 2004.
72. Seifert B, Brockmann M, Engel J, Gasser T. Fast algorithms for nonparametric curve estimation. J Comp Graph Stat 3: 192-213, 1994.
73. Shi G, Rao DC. Ignoring temporal trends in genetic effects substantially reduces power of quantitative trait linkage analysis. Genet Epidemiol 32: 61-72, 2008.
74. Singer JD, Willett JB. Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. Oxford: Oxford University Press, 2002.
75. Storey JD, Xiao W, Leek JT, Tompkins RG, Davis RW. Significance analysis of time course microarray experiments. Proc Natl Acad Sci USA 102: 12837-12842, 2005.
76. Suh YJ, Park T, Cheong SY. Linkage analysis of longitudinal data. BMC Genetics 4: S27, 2003.
77. Tang L, Song J, Belin TR, Unutzer J. A comparison of imputation methods in a longitudinal randomized clinical trial. Stat Med 24: 2111-2128, 2005. (Pubitemid 40960211)
78. The Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447: 661-678, 2007.
79. Touloumi G, Pocock SJ, Babiker AG, Darbyshire JH. Estimation and comparison of rates of change in longitudinal studies with informative drop-outs. Stat Med 18: 1215-1233, 1999.
80. Trooskens G, De Beule D, Decouttere F, Van Criekinge W. Phylogenetic trees: visualizing, customizing and detecting incongruence. Bioinformatics 21: 3801-3802, 2005. (Pubitemid 41535531)
81. Twisk J, de Vente W. Attrition in longitudinal studies. How to deal with missing data. J Clin Epidemiol 55: 329-337, 2002.
82. Venables WN, Ripley BD. Modern Applied Statistics With S. New York: Springer, 2002.
83. Venter JC, Adams MD, Myers EW, Li PW, Mural RJ, Sutton GG, Smith HO, Yandell M, Evans CA, Holt RA, Gocayne JD, Amanatides P, Ballew RM, Huson DH, Wortman JR, Zhang Q, Kodira CD, Zheng XH, Chen L, Skupski M, Subramanian G, Thomas PD, Zhang J, Gabor Miklos GL, Nelson C, Broder S, Clark AG, Nadeau J, McKusick VA, Zinder N, Levine AJ, Roberts RJ, Simon M, Slayman C, Hunkapiller M, Bolanos R, Delcher A, Dew I, Fasulo D, Flanigan M, Florea L, Halpern A, Hannenhalli S, Kravitz S, Levy S, Mobarry C, Reinert K, Remington K, Abu-Threideh J, Beasley E, Biddick K, Bonazzi V, Brandon R, Cargill M, Chandramouliswaran I, Charlab R, Chaturvedi K, Deng Z, Di Francesco V, Dunn P, Eilbeck K, Evangelista C, Gabrielian AE, Gan W, Ge W, Gong F, Gu Z, Guan P, Heiman TJ, Higgins ME, Ji RR, Ke Z, Ketchum KA, Lai Z, Lei Y, Li Z, Li J, Liang Y, Lin X, Lu F, Merkulov GV, Milshina N, Moore HM, Naik AK, Narayan VA, Neelam B, Nusskern D, Rusch DB, Salzberg S, Shao W, Shue B, Sun J, Wang Z, Wang A, Wang X, Wang J, Wei M, Wides R, Xiao C, Yan C, et al. The sequence of the human genome. Science 291: 1304-1351, 2001.
84. Verbeke G, Molenberghs G. Linear Mixed Models for Longitudinal Data. New York: Springer, 2000.
85. Wang WY, Barratt BJ, Clayton DG, Todd JA. Genome-wide association studies: theoretical and practical concerns. Nat Rev Genet 6: 109-118, 2005. (Pubitemid 40179533)
86. Wang Z, Hou W, Wu R. A statistical model to analyse quantitative trait locus interactions for HIV dynamics from the virus and human genomes. Stat Med 25: 495-511, 2006.
87. Wessel J, Schork NJ. Generalized genomic distance-based regression methodology for multilocus association analysis. Am J Hum Genet 79: 792-806, 2006.
88. Wessel J, Zapala MA, Schork NJ. Accommodating pathway information in expression quantitative trait locus analysis. Genomics 90: 132-142, 2007. (Pubitemid 46900996)
89. Witten IH, Frank E. Data Mining: Practical Machine Learning Tools and Techniques. Amsterdam: Morgan Kaufman, 2005.
90. Wolfinger RD. An example of using mixed models and PROC MIXED for longitudinal data. J Biopharm Stat 7: 481-500, 1997. (Pubitemid 27502170)
91. Won S, Elston RC, Park T. Extension of the Haseman-Elston regression model to longitudinal data. Hum Hered 61: 111-119, 2006.
92. Wu R, Lin M. Functional mapping - how to map and study the genetic architecture of dynamic complex traits. Nat Rev Genet 7: 229-237, 2006.
93. Yang J, Wu R, Casella G. Nonparametric functional mapping of quantitative trait loci. Biometrics 65: 30-39, 2009.
94. Yang Q, Chazaro I, Cui J, Guo CY, Demissie S, Larson M, Atwood LD, Cupples LA, DeStefano AL. Genetic analyses of longitudinal phenotype data: a comparison of univariate methods and a multivariate approach. BMC Genet 4, Suppl 1: S29, 2003.
95. Yang R, Tian Q, Xu S. Mapping quantitative trait loci for longitudinal traits in line crosses. Genetics 173: 2339-2356, 2006.
96. Yang X, Shoptaw S. Assessing missing data assumptions in longitudinal studies: an example using a smoking cessation trial. Drug Alcohol Depend 77: 213-225, 2005.
97. Zapala MA, Schork NJ. Multivariate regression analysis of distance matrices for testing associations between gene expression patterns and related variables. Proc Natl Acad Sci USA 103: 19430-19435, 2006.
98. Zhao W, Chen YQ, Casella G, Cheverud JM, Wu R. A non-stationary model for functional mapping of complex traits. Bioinformatics 21: 2469-2477, 2005. (Pubitemid 40731604)