Perspectives on genome-wide multi-stage family-based association studies

Statistics in Medicine

Volumn 30, Issue 18, 2011, Pages 2201-2221

  Van Steen, K ^a  

^a UNIVERSITY OF LIÈGE   (Belgium)

Author keywords

Family based association testing; Genome wide association; Multi stage designs

Indexed keywords

ARTICLE; COMPUTER PROGRAM; FALSE POSITIVE RESULT; FAMILY STUDY; GENE LINKAGE DISEQUILIBRIUM; GENETIC ANALYSIS; GENETIC ASSOCIATION; GENOTYPE; HAPLOTYPE; HUMAN; MATHEMATICAL ANALYSIS; METHODOLOGY; QUANTITATIVE TRAIT LOCUS MAPPING; REGRESSION ANALYSIS; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL ANALYSIS;

EID: 79960260455     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.4259     Document Type: Article

References (170)

1. McCarthy M, Abecasis G, Cardon L, Goldstein D, Little J, Ioannidis J, Hirschhorn J. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nature Reviews Genetics 2008; 9:356-369.
2. Sayers EW, Barrett T, Benson DA, Bolton E, Bryant SH, Canese K, Chetvernin V, Church DM, DiCuccio M, Federhen S, Feolo M, Fingerman IM, Geer LY, Helmberg W, Kapustin Y, Landsman D, Lipman DJ, Lu Z, Madden TL, Madej T, Maglott DR, Marchler-Bauer A, Miller V, Mizrachi I, Ostell J, Panchenko A, Phan L, Pruitt KD, Schuler GD, Sequeira E, Sherry ST, Shumway M, Sirotkin K, Slotta D, Souvorov A, Starchenko G, Tatusova TA, Wagner L, Wang Y, Wilbur WJ, Yaschenko E, Ye J. Database resources of the National Center for Biotechnology Information. Nucleic Acids Research 2011; 39:38-51.
3. Sherry ST, Ward MH, Kholodov M, Baker J, Phan L, Smigielski EM, Sirotkin K. dbSNP: the NCBI database of genetic variation. Nucleic Acids Research 2001; 29:308-311.
4. Consortium IHGS. Initial sequencing and analysis of the human genome (vol. 409, p. 860, 2001). Nature 2001; 411:720.
5. 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, Miklos G, 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, Francesco D, 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, Yao A, Ye J, Zhan M, Zhang W, Zhang H, Zhao Q, Zheng L, Zhong F, Zhong W, Zhu S, Zhao S, Gilbert D, Baumhueter S, Spier G, Carter C, Cravchik A, Woodage T, Ali F, An H, Awe A, Baldwin D, Baden H, Barnstead M, Barrow I, Beeson K, Busam D, Carver A, Center A, Cheng ML, Curry L, Danaher S, Davenport L, Desilets R, Dietz S, Dodson K, Doup L, Ferriera S, Garg N, Gluecksmann A, Hart B, Haynes J, Haynes C, Heiner C, Hladun S, Hostin D, Houck J, Howland T, Ibegwam C, Johnson J, Kalush F, Kline L, Koduru S, Love A, Mann F, May D, McCawley S, McIntosh T, McMullen I, Moy M, Moy L, Murphy B, Nelson K, Pfannkoch C, Pratts E, Puri V, Qureshi H, Reardon M, Rodriguez R, Rogers YH, Romblad D, Ruhfel B, Scott R, Sitter C, Smallwood M, Stewart E, Strong R, Suh E, Thomas R, Tint NN, Tse S, Vech C, Wang G, Wetter J, Williams S, Williams M, Windsor S, Winn-Deen E, Wolfe K, Zaveri J, Zaveri K, Abril JF, GuigÃ3 R, Campbell MJ, Sjolander KV, Karlak B, Kejariwal A, Mi H, Lazareva B, Hatton T, Narechania A, Diemer K, Muruganujan A, Guo N, Sato S, Bafna V, Istrail S, Lippert R, Schwartz R, Walenz B, Yooseph S, Allen D, Basu A, Baxendale J, Blick L, Caminha M, Carnes-Stine J, Caulk P, Chiang YH, Coyne M, Dahlke C, Mays A, Dombroski M, Donnelly M, Ely D, Esparham S, Fosler C, Gire H, Glanowski S, Glasser K, Glodek A, Gorokhov M, Graham K, Gropman B, Harris M, Heil J, Henderson S, Hoover J, Jennings D, Jordan C, Jordan J, Kasha J, Kagan L, Kraft C, Levitsky A, Lewis M, Liu X, Lopez J, Ma D, Majoros W, McDaniel J, Murphy S, Newman M, Nguyen T, Nguyen N, Nodell M, Pan S, Peck J, Peterson M, Rowe W, Sanders R, Scott J, Simpson M, Smith T, Sprague A, Stockwell T, Turner R, Venter E, Wang M, Wen M, Wu D, Wu M, Xia A, Zandieh A, Zhu X. The sequence of the human genome. Science 2001; 291:1304-1351.
6. Collins F, Morgan M, Patrinos A. The human genome project: lessons from large-scale biology. Science 2003; 300:286-290.
7. Consortium IH. A haplotype map of the human genome. Nature 2005; 437:1299-1320.
8. Dhand R. The 'finished' landscape. Nature 2006; 7:S1.
9. Cardon LR, Palmer LJ. Population stratification and spurious allelic association. Lancet 2003; 361:598-604.
10. Cardon LR, Bell JI. Association study designs for complex diseases. Nature Reviews Genetics 2001; 2:91-99.
11. Laird NM, Horvath S, Xu X. Implementing a unified approach to family-based tests of association. Genetic Epidemiology 2000; 19(1):S36-S42.
12. Laird N, Lange C. The role of family-based designs in genome-wide association studies. Statistical Science 2009; 24:388-397.
13. Devlin B, Roeder K. Genomic control for association studies. Biometrics 1999; 55:997-1004.
14. Pritchard JK, Stephens M, Rosenberg NA, Donnelly P. Association mapping in structured populations. American Journal of Human Genetics 2000; 67:170-181.
15. Li MY, Reilly MP, Rader DJ, Wang LS. Correcting population stratification in genetic association studies using a phylogenetic approach. Bioinformatics 2010; 26:798-806.
16. Risch N, Merikangas K. The future of genetic studies of complex human diseases. Science 1996; 273:1516-1517.
17. Ozaki K. Myocardial infarction. Nature Genetics 2002; 32:650-654.
18. Manolio T, Brooks L, Collins F. A HapMap harvest of insights into the genetics of common disease. Journal of Clinical Investigation 2008; 118:1590-1605.
19. Seng KC, Seng CK. The success of the genome-wide association approach: a brief story of a long struggle. European Journal of Human Genetics 2008; 16:554-564.
20. Bodmer W, Bonilla C. Common and rare variants in multifactorial susceptibility to common diseases. Nature Genetics 2008; 40:695-701.
21. Clark AG, Li J. Conjuring SNPs to detect association. Nature Genetics 2007; 39:813-816.
22. Kraft P, Cox D. Study designs for genome-wide association studies. Advances in Genetics 2008; 60:465-504.
23. Thomas DC, Casey G, Conti DV, Haile RW, Lewinger JP, Stram DO. Methodological issues in multistage genome-wide association studies. Statistical Science 2009; 24:414-429.
24. Pearson T, Manolio T. How to interpret a genome-wide association study. JAMA 2008; 299:1335-1344.
25. Spielman RS, McGinnis RE, Ewens WJ. Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). American Journal of Human Genetics 1993; 52:506-516.
26. Fulker DW, Cherny SS, Sham PC, Hewitt JK. Combined linkage and association sib-pair analysis for quantitative traits. American Journal of Human Genetics 1999; 64:259-267.
27. Hardy J, Singleton A. Genomewide association studies and human disease. New England Journal of Medicine 2009; 360:1759-1768.
28. Hirschhorn J. Genomewide association studies-illuminating biologic pathways. New England Journal of Medicine 2009; 360:1699-1701.
29. Hirschhorn JN, Daly MJ. Genome-wide association studies for common diseases and complex traits. Nature Reviews Genetics 2005; 6:95-108.
30. Group GAINCR, Manolio T, Rodriguez L, Brooks L, Abecasis G. of Psoriasis CAS, Ballinger D, Daly M, Donnelly P, Faraone S. Project IM-CAG, Frazer K, Gabriel S, Gejman P. of Schizophrenia Collaboration M, Guttmacher A, Harris E, Insel T, Kelsoe J, Study B, Lander E, McCowin N, Mailman M, Nabel E, Ostell J, Pugh E, Sherry S, Sullivan P. in Population-Based Samples Study MDSGA, Thompson J, Warram J. of Kidneys in Diabetes GoKinD Study G, Wholley D, Milos P, Collins F. New models of collaboration in genome-wide association studies: the Genetic Association Information Network. Nature Genetics 2007; 39:1045-1051.
31. Barrett J, Hansoul S, Nicolae D, Cho J, Duerr R, Rioux J, Brant S, Silverberg M, Taylor K, Barmada M, Bitton A, Dassopoulos T, Datta L, Green T, Griffiths A, Kistner E, Murtha M, Regueiro M, Rotter J, Schumm P, Steinhart H, Targan S, Xavier R. Consortium NIDDKIBDG, Libioulle Cc, Sandor C, Lathrop M, Belaiche J, Dewit O, Gut I, Heath S, Laukens D, Mni M, Rutgeerts P, Gossum A, Zelenika D, Franchimont D, Hugot J-P, de Vos M, Vermeire S, Louis E. Consortium B-FIBD, Consortium WTCC, Cardon L, Anderson C, Drummond H, Nimmo E, Ahmad T, Prescott N, Onnie C, Fisher S, Marchini J, Ghori J, Bumpstead S, Gwilliam R, Tremelling M, Deloukas P, Mansfield J, Jewell D, Satsangi J, Mathew C, Parkes M, Georges M, Daly M. Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease. Nature Genetics 2008; 40:955-962.
32. Manolio T, Collins F, Cox N, Goldstein D, Hindorff L, Hunter D, McCarthy M, Ramos E, Cardon L, Chakravarti A, Cho J, Guttmacher A, Kong A, Kruglyak L, Mardis E, Rotimi C, Slatkin M, Valle D, Whittemore A, Boehnke M, Clark A, Eichler E, Gibson G, Haines J, Mackay T, McCarroll S, Visscher P. Finding the missing heritability of complex diseases. Nature 2009; 461:747-753.
33. Gordon D, Finch S. Factors affecting statistical power in the detection of genetic association. Journal of Clinical Investigation 2005; 115:1408-1418.
34. Service S, Sandkuijl L, Freimer N. Cost-effective designs for linkage disequilibrium mapping of complex traits. American Journal of Human Genetics 2003; 72:1213-1220.
35. Thomas D. Are we ready for genome-wide association studies? Cancer Epidemiology, Biomarkers and Prevention 2006; 15:595-598.
36. Satagopan J, Elston R. Optimal two-stage genotyping in population-based association studies? Genetic Epidemiology 2003; 25:149-157.
37. Satagopan J, Venkatraman ES, Begg C. Two-stage designs for gene-disease association studies with sample size constraints. Biometrics 2004; 60:589-597.
38. Satagopan J, Verbel D, Venkatraman ES, Offit K, Begg C. Two-stage designs for gene-disease association studies. Biometrics 2002; 58:163-170.
39. Wang H, Thomas D, Pe'er I, Stram D. Optimal two-stage genotyping designs for genome-wide association scans. Genetic Epidemiology 2006; 30:356-368.
40. Skol A, Scott L, Abecasis Ga, Boehnke M. Optimal designs for two-stage genome-wide association studies. Genetic Epidemiology 2007; 31:776-788.
41. Visscher P, Andrew T, Nyholt D. Genome-wide association studies of quantitative traits with related individuals: little (power) lost but much to be gained. European Journal of Human Genetics 2008; 16:387-390.
42. McArdle PF, O'Connell JR, Pollin TI, Baumgarten M, Shuldiner AR, Peyser PA, Mitchell BD. Accounting for relatedness in family based genetic association studies. Human Heredity 2007; 64:234-242.
43. Fardo D, Ionita-Laza I, Lange C. On quality control measures in genome-wide association studies: a test to assess the genotyping quality of individual probands in family-based association studies and an application to the HapMap data. PLoS Genet 2009; 5(7):e1000572.
44. Plomin R, Haworth C, Davis O. Common disorders are quantitative traits. Nature Reviews Genetics 2009; 10:872-878.
45. Fisher RA. The correlation between relatives on the superposition of Mendelian inheritance. Transactions of the Royal Society of Edinburgh 1918; 52:399-433.
46. Frazer K, Murray S, Schork N, Topol E. Human genetic variation and its contribution to complex traits. Nature Reviews Genetics 2009; 10:241-251.
47. Mackay T, Stone E, Ayroles J. The genetics of quantitative traits: challenges and prospects. Nature Reviews Genetics 2009; 10:565-577.
48. Mackay TF. The genetic architecture of quantitative traits. Annual Review of Genetics 2001; 35:303-339.
49. Amos CI. Robust variance-components approach for assessing genetic linkage in pedigrees. American Journal of Human Genetics 1994; 54:535-543.
50. Broman KW. Review of statistical methods for QTL mapping in experimental crosses. Laboratory Animal (NY) 2001; 30:44-52.
51. Majumder P, Ghosh S. Mapping quantitative trait loci in humans: achievements and limitations. Journal of Clinical Investigation 2005; 115:1419-1424.
52. Haseman JK, Elston RC. The investigation of linkage between a quantitative trait and marker loci. Behavior Genetics 1972; 2(1):3-19.
53. Sham PC, Cherny SS, Purcell S, Hewitt JK. Power of linkage versus association analysis of quantitative traits, by use of variance-components models, for sibship data. American Journal of Human Genetics 2000; 66:1616-1630.
54. Ewens W, Li M, Spielman R. A review of family-based tests for linkage disequilibrium between a quantitative trait and a genetic marker. PLoS Genetics 2008; 4:e1000180.
55. Gordon D, Devoto M. Advances in family-based association analysis. Introduction. Human Heredity 2008; 66:65-66.
56. Laird N, Lange C. Family-based methods for linkage and association analysis. Advances in Genetics 2008; 60:219-252.
57. Spielman RS, Ewens WJ. The TDT and other family-based tests for linkage disequilibrium and association. American Journal of Human Genetics 1996; 59:983-989.
58. Whittaker JC, Morris AP. Family-based tests of association and/or linkage. Annals of Human Genetics 2001; 65:407-419.
59. Zhao H. Family-based association studies. Statistical Methods in Medical Research 2000; 9:563-587.
60. Sham PC, Curtis D. An extended transmission/disequilibrium test (TDT) for multi-allele marker loci. Annals of Human Genetics 1995; 59:323-336.
61. Cleves MA, Olson JM, Jacobs KB. Exact transmission-disequilibrium tests with multiallelic markers. Genetic Epidemiology 1997; 14:337-347.
62. Rabinowitz D. A transmission disequilibrium test for quantitative trait loci. Human Heredity 1997; 47:342-350.
63. Curtis D. Use of siblings as controls in case-control association studies (vol. 61, p. 319, 1997). Annals of Human Genetics 1998; 62:89.
64. Curtis D. Use of siblings as controls in case-control association studies. Annals of Human Genetics 1997; 61:319-333.
65. Martin E, Bass M, Hauser E, Kaplan N. Accounting for linkage in family-based tests of association with missing parental genotypes. American Journal of Human Genetics 2003; 73:1016-1026.
66. Martin ER, Bass MP, Gilbert JR, Pericak-Vance MA, Hauser ER. Genotype-based association test for general pedigrees: the genotype-PDT. Genetic Epidemiology 2003; 25:203-213.
67. Martin ER, Bass MP, Kaplan NL. Correcting for a potential bias in the pedigree disequilibrium test. American Journal of Human Genetics 2001; 68:1065-1067.
68. Martin ER, Kaplan NL, Weir BS. Tests for linkage and association in nuclear families. American Journal of Human Genetics 1997; 61:439-448.
69. Martin ER, Monks SA, Warren LL, Kaplan NL. A test for linkage and association in general pedigrees: the pedigree disequilibrium test. American Journal of Human Genetics 2000; 67:146-154.
70. Zhang S, Zhang K, Li J, Sun F, Zhao H. Test of association for quantitative traits in general pedigrees: the quantitative pedigree disequilibrium test. Genetic Epidemiology 2001; 21(Suppl. 1):S370-S375.
71. Spielman RS, Ewens WJ. A sibship test for linkage in the presence of association: the sib transmission/disequilibrium test. American Journal of Human Genetics 1998; 62:450-458.
72. Horvath S, Laird NM. A discordant-sibship test for disequilibrium and linkage: no need for parental data. American Journal of Human Genetics 1998; 63:1886-1897.
73. Knapp M. The transmission/disequilibrium test and parental-genotype reconstruction: the reconstruction-combined transmission/disequilibrium test. American Journal of Human Genetics 1999; 64:861-870.
74. Allison DB, Heo M, Kaplan N, Martin ER. Sibling-based tests of linkage and association for quantitative traits. American Journal of Human Genetics 1999; 64:1754-1763.
75. Clayton D, Jones H. Transmission/disequilibrium tests for extended marker haplotypes. American Journal of Human Genetics 1999; 65:1161-1169.
76. Betensky RA, Rabinowitz D. Simple approximations for the maximal transmission/disequilibrium test with a multi-allelic marker. Annals of Human Genetics 2000; 64:567-574.
77. Dudbridge F, Koeleman BP, Todd JA, Clayton DG. Unbiased application of the transmission/disequilibrium test to multilocus haplotypes. American Journal of Human Genetics 2000; 66:2009-2012.
78. Abecasis GR, Cardon LR, Cookson WO. A general test of association for quantitative traits in nuclear families. American Journal of Human Genetics 2000; 66:279-292.
79. Abecasis GR, Cookson WO, Cardon LR. Pedigree tests of transmission disequilibrium. European Journal of Human Genetics 2000; 8:545-551.
80. Rabinowitz D, Laird N. A unified approach to adjusting association tests for population admixture with arbitrary pedigree structure and arbitrary missing marker information. Human Heredity 2000; 50:211-223.
81. Horvath S, Laird NM, Knapp M. The transmission/disequilibrium test and parental-genotype reconstruction for X-chromosomal markers. American Journal of Human Genetics 2000; 66:1161-1167.
82. Seltman H, Roeder K, Devlin B. Transmission/disequilibrium test meets measured haplotype analysis: family-based association analysis guided by evolution of haplotypes. American Journal of Human Genetics 2001; 68:1250-1263.
83. Liu Y, Jansen G, Lin C. The covariance between relatives conditional on genetic markers. Genetics Selection Evolution 2002; 34:657-678.
84. Lange C, Silverman E, Xu X, Weiss S, Laird N. A multivariate family-based association test using generalized estimating equations: FBAT-GEE. Biostatistics 2003; 4:195-206.
85. Lange C, van Steen K, Andrew T, Lyon H, DeMeo D, Raby B, Murphy A, Silverman E, MacGregor A, Weiss S, Laird N. A family-based association test for repeatedly measured quantitative traits adjusting for unknown environmental and/or polygenic effects. Statistical Applications in Genetics and Molecular Biology 2004; 3(1). Article No. 17.
86. Purcell S, Sham P, Daly M. Parental phenotypes in family-based association analysis. American Journal of Human Genetics 2005; 76:249-259.
87. Whittemore A, Halpern J, Ahsan H. Covariate adjustment in family-based association studies. Genetic Epidemiology 2005; 28:244-255.
88. Schneiter K, Laird N, Corcoran C. Exact family-based association tests for biallelic data. Genetic Epidemiology 2005; 29:185-194.
89. Diao G, Lin DY. Improving the power of association tests for quantitative traits in family studies. Genetic Epidemiology 2006; 30:301-313.
90. Martin ER, Ritchie MD, Hahn L, Kang S, Moore JH. A novel method to identify gene-gene effects in nuclear families: the MDR-PDT. Genetic Epidemiology 2006; 30:111-123.
91. Rakovski C, Xu X, Lazarus R, Blacker D, Laird N. A new multimarker test for family-based association studies. Genetic Epidemiology 2007; 31:9-17.
92. Xu X, Rakovski C, Laird N. An efficient family-based association test using multiple markers. Genetic Epidemiology 2006; 30:620-626.
93. Rakovski C, Weiss S, Laird N, Lange C. FBAT-SNP-PC: an approach for multiple markers and single trait in family-based association tests. Human Heredity 2008; 66:122-126.
94. Ding X, Laird N. Family-based association tests with longitudinal measurements: handling missing data. Human Heredity 2009; 68:98-105.
95. Ding X, Lange C, Xu X, Laird N. New powerful approaches for family-based association tests with longitudinal measurements. Annals of Human Genetics 2009; 73:74-83.
96. Lange C, DeMeo D, Laird N. Power and design considerations for a general class of family-based association tests: quantitative traits. American Journal of Human Genetics 2002; 71:1330-1341.
97. Lange C, Laird N. Power calculations for a general class of family-based association tests: dichotomous traits. American Journal of Human Genetics 2002; 71:575-584.
98. Horvath S, Xu X, Laird NM. The family based association test method: strategies for studying general genotype-phenotype associations. European Journal of Human Genetics 2001; 9:301-306.
99. Van Steen K, Lange C. PBAT: a comprehensive software package for genome-wide association analysis of complex family-based studies. Human Genomics 2005; 2:67-69.
100. Van Steen K, McQueen M, Herbert A, Raby B, Lyon H, Demeo D, Murphy A, Su J, Datta S, Rosenow C, Christman M, Silverman E, Laird N, Weiss S, Lange C. Genomic screening and replication using the same data set in family-based association testing. Nature Genetics 2005; 37:683-691.
101. Thompson EA. Inference of genealogical structure. Social Science Information 1976; 15:477-526.
102. Ziegler SG, König I. A Statistical Approach to Genetic Epidemiology-Concepts and Applications (2nd edn). Wiley-Blackwell: New York, 2010.
103. Boerwinkle E, Chakraborty R, Sing CF. The use of measured genotype information in the analysis of quantitative phenotypes in man. I. Models and analytical methods. Annals of Human Genetics 1986; 50:181-194.
104. Sham PC. Statistics in Human Genetics. Arnold: London, 1998.
105. Abecasis GR, Cookson WO, Cardon LR. The power to detect linkage disequilibrium with quantitative traits in selected samples. American Journal of Human Genetics 2001; 68:1463-1474.
106. Yu J, Pressoir G, Briggs W, Bi I, Yamasaki M, Doebley J, McMullen M, Gaut B, Nielsen D, Holland J, Kresovich S, Buckler E. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genetics 2006; 38:203-208.
107. Lange C, DeMeo D, Silverman E, Weiss S, Laird N. Using the noninformative families in family-based association tests: a powerful new testing strategy. American Journal of Human Genetics 2003; 73:801-811.
108. Lange C, Lyon H, DeMeo D, Raby B, Silverman E, Weiss S. A new powerful non-parametric two-stage approach for testing multiple phenotypes in family-based association studies. Human Heredity 2003; 56:10-17.
109. Laird N, Lange C. Family-based designs in the age of large-scale gene-association studies. Nature Reviews Genetics 2006; 7:385-394.
110. Ionita-Laza I, McQueen M, Laird N, Lange C. Genomewide weighted hypothesis testing in family-based association studies, with an application to a 100K scan. American Journal of Human Genetics 2007; 81:607-614.
111. Murphy A, Weiss S, Lange C. Screening and replication using the same data set: testing strategies for family-based studies in which all probands are affected. PLoS Genetics 2008; 4(9):e1000197.
112. Murphy A, Weiss ST, Lange C. Two-stage testing strategies for genome-wide association studies in family-based designs. Methods in Molecular Biology 2010; 620:485-496.
113. Aulchenko Y, de Koning D-J, Haley C. Genomewide rapid association using mixed model and regression: a fast and simple method for genomewide pedigree-based quantitative trait loci association analysis. Genetics 2007; 177:577-585.
114. Amin N, van Duijn C, Aulchenko Y. A genomic background based method for association analysis in related individuals. PLoS One 2007; 2(12):e1274.
115. Chen W-M, Abecasis G. Family-based association tests for genomewide association scans. American Journal of Human Genetics 2007; 81:913-926.
116. Morton NE. Sequential tests for the detection of linkage. American Journal of Human Genetics 1955; 7:277-318.
117. Lake SL, Blacker D, Laird NM. Family-based tests of association in the presence of linkage. American Journal of Human Genetics 2000; 67:1515-1525.
118. Dubé M-P, Schmidt S, Hauser E, Darabi H, Li J, Barhdadi A, Wang X, Sha Q, Zhang Z, Wang T, Aschard H, Guedj M, Rohlfs R, Anderson A, Taylor C, Mirea L, Nickolov R, Milanov V, Yang H-C, Song Y, Sinha R. Multistage designs in the genomic era: providing balance in complex disease studies. Genetic Epidemiology 2007; 31(Suppl. 1):S118-S123.
119. Cattaert T, Urrea V, Naj AC, De Lobel L, De Wit V, Fu M, John JMM, Shen HQ, Calle ML, Ritchie MD, Edwards TL, Van Steen K. FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals. PLoS One 2010; 5.
120. Macgregor S, Khan I. GAIA: an easy-to-use web-based application for interaction analysis of case-control data. BMC Medical Genetics 2006; 7:34.
121. Marchini J, Donnelly P, Cardon L. Genome-wide strategies for detecting multiple loci that influence complex diseases. Nature Genetics 2005; 37:413-417.
122. Strobl C, Boulesteix A-L, Kneib T, Augustin T, Zeileis A. Conditional variable importance for random forests. BMC Bioinformatics 2008; 9:307.
123. Aschard H, Guedj Ml, Demenais F. A two-step multiple-marker strategy for genome-wide association studies. BMC Proceedings 2007; 1(Suppl. 1):S134.
124. Yang H-C, Hsieh H-Y, Fann C. Kernel-based association test. Genetics 2008; 179:1057-1068.
125. Li J. Marker selection for whole-genome association studies with two-stage designs using dense single-nucleotide polymorphisms. BMC Proceedings 2007; 1(Suppl. 1).
126. Chanda P, Sucheston L, Liu S, Zhang A, Ramanathan M. Information-theoretic gene-gene and gene-environment interaction analysis of quantitative traits. BMC Genomics 2009; 10:509.
127. Chanda P, Sucheston L, Zhang A, Brazeau D, Freudenheim J, Ambrosone C, Ramanathan M. AMBIENCE: a novel approach and efficient algorithm for identifying informative genetic and environmental associations with complex phenotypes. Genetics 2008; 180:1191-1210.
128. Chanda P, Sucheston L, Zhang A, Ramanathan M. The interaction index, a novel information-theoretic metric for prioritizing interacting genetic variations and environmental factors. European Journal of Human Genetics 2009; 17:1274-1286.
129. Chanda P, Zhang A, Brazeau D, Sucheston L, Freudenheim J, Ambrosone C, Ramanathan M. Information-theoretic metrics for visualizing gene-environment interactions. American Journal of Human Genetics 2007; 81:939-963.
130. Chanda P, Zhang A, Sucheston L, Ramanathan M. A two-stage search strategy for detecting multiple loci associated with rheumatoid arthritis. BMC Proceedings 2009; 3(Suppl. 7):S72.
131. Geurts P, Ernst D, Wehenkel L. Extremely randomized trees. Machine Learning 2006; 36:3-42.
132. Schwarz D, Szymczak S, Ziegler A, König I. Evaluation of single-nucleotide polymorphism imputation using random forests. BMC Proceedings 2009; 3(Suppl. 7):S65.
133. Wang T, Lu Q, Torres-Caban M, Elston R. Two-stage analysis strategy for identifying the IgM quantitative trait locus. BMC Proceedings 2007; 1(Suppl. 1):S139.
134. Nguyen T, Pahl R, Schäfer H. Optimal robust two-stage designs for genome-wide association studies. Annals of Human Genetics 2009; 73:638-651.
135. Li J. Prioritize and select SNPs for association studies with multi-stage designs. Journal of Computational Biology 2008; 15:241-257.
136. Kraft P. Efficient two-stage genome-wide association designs based on false positive report probabilities. Pacific Symposium on Biocomputing, vol. 11, 2006; 523-534.
137. Wakefield J. Bayes factors for genome-wide association studies: comparison with P-values. Genetic Epidemiology 2009; 33:79-86.
138. Gail MH, Pfeiffer RM, Wheeler W, Pee D. Probability that a two-stage genome-wide association study will detect a disease-associated snp and implications for multistage designs. Annals of Human Genetics 2008; 72:812-820.
139. Roeder K, Devlin B, Wasserman L. Improving power in genome-wide association studies: weights tip the scale. Genetic Epidemiology 2007; 31:741-747.
140. Moerkerke B, Goetghebeur E. Optimal screening for promising genes in 2-stage designs. Biostatistics 2008; 9:700-714.
141. Boulesteix A-L, Slawski M. Stability and aggregation of ranked gene lists. Briefings in Bioinformatics 2009; 10:556-568.
142. Wang H, Stram D. Optimal two-stage genome-wide association designs based on false discovery rate. Briefings in Bioinformatics 2006; 51:457-465.
143. Zehetmayer S, Bauer P, Posch M. Optimized multi-stage designs controlling the false discovery or the family-wise error rate. Statistics in Medicine 2008; 27:4145-4160.
144. Storey J, Tibshirani R. Statistical significance for genomewide studies. Proceedings of the National Academy of Sciences of the United States of America 2003; 100:9440-9445.
145. Wakefield J. A Bayesian measure of the probability of false discovery in genetic epidemiology studies. American Journal of Human Genetics 2007; 81:208-227.
146. Pocock SJ. Group sequential methods in the design and analysis of clinical trials. Biometrika 1977; 64:191-199.
147. König IR, Schäfer H, Müller HH, Ziegler A. Optimized group sequential study designs for tests of genetic linkage and association in complex diseases. American Journal of Human Genetics 2001; 69:590-600.
148. Boddeker IR, Ziegler A. Sequential designs for genetic epidemiological linkage or association studies-a review of the literature. Biometrical Journal 2001; 43:501-525.
149. Bauer P. Adaptive designs: looking for a needle in the haystack-a new challenge in medical research. Statistics in Medicine 2008; 27:1565-1580.
150. Kelly P, Zhou Y, Whitehead J, Stallard N, Bowman C. Sequentially testing for a gene-drug interaction in a genomewide analysis. Statistics in Medicine 2008; 27:2022-2034.
151. Wang X, Zhang Z, Zhang S, Sha Q. Genome-wide association tests by two-stage approaches with unified analysis of families and unrelated individuals. BMC Proceedings 2007; 1(Suppl. 1):S140.
152. Ioannidis JP. Non-replication and inconsistency in the genome-wide association setting. Human Heredity 2007; 64:203-213.
153. Ioannidis JP, Patsopoulos NA, Evangelou E. Heterogeneity in meta-analyses of genome-wide association investigations. PLoS One 2007; 2:e841.
154. Galvan A, Ioannidis JP, Dragani TA. Beyond genome-wide association studies: genetic heterogeneity and individual predisposition to cancer. Trends in Genetics 2010; 26:132-141.
155. Moonesinghe R, Khoury MJ, Liu T, Ioannidis JP. Required sample size and nonreplicability thresholds for heterogeneous genetic associations. Proceedings of the National Academy of Sciences of the United States of America 2008; 105:617-622.
156. Skol A, Scott L, Abecasis Ga, Boehnke M. Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies. Nature Genetics 2006; 38:209-213.
157. Schmidt M, Qin X, Martin E, Hauser E, Schmidt S. Two-stage study designs for analyzing disease-associated covariates: linkage thresholds and case-selection strategies. BMC Proceedings 2007; 1(Suppl. 1):S138.
158. Thomas DC, Siemiatycki J, Dewar R, Robins J, Goldberg M, Armstrong BG. The problem of multiple inference in studies designed to generate hypotheses. American Journal of Epidemiology 1985; 122:1080-1095.
159. Macgregor S. Optimal two-stage testing for family-based genome-wide association studies. American Journal of Human Genetics 2008; 82(3):797-799.
160. Ionita-Laza I, McQueen M, Weiss S, Laird N, Lange C. Response to Macgregor. American Journal of Human Genetics 2008; 82:799-800.
161. Rohlfs R, Taylor C, Mirea L, Bull S, Corey M, Anderson A. One-stage design is empirically more powerful than two-stage design for family-based genome-wide association studies. BMC Proceedings 2007; 1(Suppl. 1):S137.
162. Won S, Bertram L, Becker D, Tanzi RE, Lange C. Maximizing the power of genome-wide association studies: a novel class of powerful family-based association tests. Statistics in Biosciences 2009; 1:125-143.
163. Moore J, Ritchie M. The challenges of whole-genome approaches to common diseases. JAMA 2004; 291:1642-1643.
164. Szymczak S, Igl BW, Ziegler A. Detecting SNP-expression associations: A comparison of mutual information and median test with standard statistical approaches. Statistics in Medicine 2009; 28:3581-3596.
165. Leutenegger A-L, Prum B, Génin E, Verny C, Lemainque A, Clerget-Darpoux Fo, Thompson E. Estimation of the inbreeding coefficient through use of genomic data. American Journal of Human Genetics 2003; 73:516-523.
166. Weir B, Anderson A, Hepler A. Genetic relatedness analysis: modern data and new challenges. Nature Reviews Genetics 2006; 7:771-780.
167. Bartlett MS. Properties of sufficiency and statistical tests. Proceedings of the Royal Society A 1937; 160:268-282.
168. Feng T, Zhang S, Sha Q. Two-stage association tests for genome-wide association studies based on family data with arbitrary family structure. European Journal of Human Genetics 2007; 15:1169-1175.
169. Ionita I, Man M. Optimal two-stage strategy for detecting interacting genes in complex diseases. BMC Genetics 2006; 7:39.
170. Moore JH, Williams SM. Traversing the conceptual divide between biological and statistical epistasis: Systems biology and a more modern synthesis. Bioessays 2005; 27:637-646.