On a general class of conditional tests for family-based association studies in genetics: the asymptotic distribution, the conditional power, and optimality considerations
Family‐based association tests (FBATs) provide simple and powerful tests to detect association between a genetic marker and a disease‐susceptibility locus, manifest in subjects by a phenotype or disease trait. Here we propose a new class of conditional tests for family‐based association studies that...
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| Published in | Genetic epidemiology Vol. 23; no. 2; pp. 165 - 180 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Wiley Subscription Services, Inc., A Wiley Company
01.08.2002
Wiley-Liss |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0741-0395 1098-2272 |
| DOI | 10.1002/gepi.209 |
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| Abstract | Family‐based association tests (FBATs) provide simple and powerful tests to detect association between a genetic marker and a disease‐susceptibility locus, manifest in subjects by a phenotype or disease trait. Here we propose a new class of conditional tests for family‐based association studies that includes most of the established tests and their generalizations. The class of tests is very general; it can be applied to longitudinal and multivariate traits or phenotypes, multiple genetic markers, and many other situations not yet discussed in the literature. For any test in this class, we derive the asymptotic distribution under the null hypothesis, the conditional power under any alternative hypothesis, and the optimal offset for single degree of freedom tests. The proposed methodology is illustrated with a genetic study of asthma. Genet. Epidemiol. 23:165–180, 2002. © 2002 Wiley‐Liss, Inc. |
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| AbstractList | Family‐based association tests (FBATs) provide simple and powerful tests to detect association between a genetic marker and a disease‐susceptibility locus, manifest in subjects by a phenotype or disease trait. Here we propose a new class of conditional tests for family‐based association studies that includes most of the established tests and their generalizations. The class of tests is very general; it can be applied to longitudinal and multivariate traits or phenotypes, multiple genetic markers, and many other situations not yet discussed in the literature. For any test in this class, we derive the asymptotic distribution under the null hypothesis, the conditional power under any alternative hypothesis, and the optimal offset for single degree of freedom tests. The proposed methodology is illustrated with a genetic study of asthma. Genet. Epidemiol. 23:165–180, 2002. © 2002 Wiley‐Liss, Inc. Family-based association tests (FBATs) provide simple and powerful tests to detect association between a genetic marker and a disease-susceptibility locus, manifest in subjects by a phenotype or disease trait. Here we propose a new class of conditional tests for family-based association studies that includes most of the established tests and their generalizations. The class of tests is very general; it can be applied to longitudinal and multivariate traits or phenotypes, multiple genetic markers, and many other situations not yet discussed in the literature. For any test in this class, we derive the asymptotic distribution under the null hypothesis, the conditional power under any alternative hypothesis, and the optimal offset for single degree of freedom tests. The proposed methodology is illustrated with a genetic study of asthma. Family-based association tests (FBATs) provide simple and powerful tests to detect association between a genetic marker and a disease-susceptibility locus, manifest in subjects by a phenotype or disease trait. Here we propose a new class of conditional tests for family-based association studies that includes most of the established tests and their generalizations. The class of tests is very general; it can be applied to longitudinal and multivariate traits or phenotypes, multiple genetic markers, and many other situations not yet discussed in the literature. For any test in this class, we derive the asymptotic distribution under the null hypothesis, the conditional power under any alternative hypothesis, and the optimal offset for single degree of freedom tests. The proposed methodology is illustrated with a genetic study of asthma.Family-based association tests (FBATs) provide simple and powerful tests to detect association between a genetic marker and a disease-susceptibility locus, manifest in subjects by a phenotype or disease trait. Here we propose a new class of conditional tests for family-based association studies that includes most of the established tests and their generalizations. The class of tests is very general; it can be applied to longitudinal and multivariate traits or phenotypes, multiple genetic markers, and many other situations not yet discussed in the literature. For any test in this class, we derive the asymptotic distribution under the null hypothesis, the conditional power under any alternative hypothesis, and the optimal offset for single degree of freedom tests. The proposed methodology is illustrated with a genetic study of asthma. |
| Author | Laird, Nan M. Lange, Christoph |
| Author_xml | – sequence: 1 givenname: Christoph surname: Lange fullname: Lange, Christoph email: clange@hsph.harvard.edu organization: Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts – sequence: 2 givenname: Nan M. surname: Laird fullname: Laird, Nan M. organization: Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts |
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| References | Lunetta K, Faraone S, Biederman J, Laird N. 2000. Family-based tests of association and linkage that use unaffected sibs, covariates, and interactions. Am J Hum Genet 66:605-14. Serfling R. 1980. Approximation theorems of mathematical statistics. New York: Wiley. Sham P. 1997. Statistics in human genetics. Arnold. Allison DB, Heo M, Kaplan N, Martin ER. 1999. Sibling-based tests of linkage and association for quantitive traits. Am J Hum Genet 64:1754-64. Rabinowitz D. 1997. A transmission disequilibrium test for quantitative trait loci. Hum Hered 47:1113-8. Lange C, Silverman E, Weiss S, Xu X, Laird N. 2001. A multivariate transmission disequilibrium test. Biostatistics [In press]. Rabinowitz D, Laird N. 2000. A unified approach to adjusting association tests for population admixture with arbitrary pedigree structure and arbitrary missing marker information. Hum Hered 50:211-23. Horvath S, Xu X, Laird N. 2001. The family based association test method: strategies for studying general genotype-phenotype associations. Eur J Hum Genet 9:301-6. Horvath S, Laird NM. 1998. A discordant-sibship test for disequilibrium and linkage: no need for parental data. Am J Hum Genet 63:1886-97. Petrov V. 1995. Sums of independent random variables. Berlin: Springer. Balding D, Bishop M, Cannings C. 2001. Handbook of statistical genetics. New York: John Wiley. Laird N, Horvath S, Xu X. 2000. Implementing a unified approach to family based tests of association. Genet Epidemiol [Suppl] 19:36-42. Spielman R, McGinnis R, Ewens WJ. 1993. Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (iddm). Am J Hum Genet 52:506-16. Lake S, Blacker D, Laird N. 2000. Family-based tests of association in the presence of linkage. Am J Hum Genet 67:1515-25. Billingsley P. 1995. Probability and measure. New York: John Wiley. Cox DR, Hinkley DV. 1979. Theoretical statistics. New York: Chapman and Hall. Lazzeroni L, Lange K. 2001. A conditional inference framework for extending the transmission/disequilibrium test. Hum Hered 48:67-81. Lange C, Laird NM. 2002. Power calculations for a general class of family-based association tests. AJHG [In press]. McGinnis R. 2000. General equations for pt, ps, and the power of the tdt and the affected sib-pair test. Am J Hum Genet 67:1340-7. Allison DB. 1997. Transmission-disequilibrium tests for quantitive traits. Am J Hum Genet 60:676-90. Boehnke M, Langefeld CD. 1998. Genetic association mapping based on discordant sib pairs: the discordant-alleles test. Am J Hum Genet 62:950-61. Risch N. 2000. Searching for genetic determinants in the new millennium. Nature 405:847-56. Falconer DS, Mackay TFC. 1997. Introduction to quantitative genetics. Longman. Whittemore A, Tu I. 2000, Detection of disease genes by use of family data. Likelihood-based theory. Am J Hum Genet 66:1328-40. 2000; 19 1997; 60 2001 2000; 67 2000; 66 1997; 47 2001; 9 2000; 405 1993; 52 2000; 50 1997 1995 1999; 64 2001; 48 2002 1980 1998; 63 1998; 62 1979 Allison DB (e_1_2_1_2_1) 1997; 60 Petrov V (e_1_2_1_20_1) 1995 Falconer DS (e_1_2_1_9_1) 1997 Clayton D (e_1_2_1_7_1) 2001 Laird N (e_1_2_1_13_1) 2000; 19 McGinnis R (e_1_2_1_19_1) 2000; 67 Sham P (e_1_2_1_25_1) 1997 e_1_2_1_23_1 e_1_2_1_24_1 e_1_2_1_21_1 e_1_2_1_22_1 e_1_2_1_27_1 e_1_2_1_28_1 Billingsley P (e_1_2_1_5_1) 1995 Balding D (e_1_2_1_4_1) 2001 e_1_2_1_8_1 Spielman R (e_1_2_1_26_1) 1993; 52 e_1_2_1_6_1 Lange C (e_1_2_1_15_1) 2002 e_1_2_1_3_1 e_1_2_1_12_1 e_1_2_1_10_1 e_1_2_1_11_1 Lange C (e_1_2_1_16_1) 2001 e_1_2_1_17_1 e_1_2_1_14_1 e_1_2_1_18_1 |
| References_xml | – reference: Cox DR, Hinkley DV. 1979. Theoretical statistics. New York: Chapman and Hall. – reference: Lunetta K, Faraone S, Biederman J, Laird N. 2000. Family-based tests of association and linkage that use unaffected sibs, covariates, and interactions. Am J Hum Genet 66:605-14. – reference: Spielman R, McGinnis R, Ewens WJ. 1993. Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (iddm). Am J Hum Genet 52:506-16. – reference: Balding D, Bishop M, Cannings C. 2001. Handbook of statistical genetics. New York: John Wiley. – reference: Horvath S, Laird NM. 1998. A discordant-sibship test for disequilibrium and linkage: no need for parental data. Am J Hum Genet 63:1886-97. – reference: Horvath S, Xu X, Laird N. 2001. The family based association test method: strategies for studying general genotype-phenotype associations. Eur J Hum Genet 9:301-6. – reference: Lange C, Silverman E, Weiss S, Xu X, Laird N. 2001. A multivariate transmission disequilibrium test. Biostatistics [In press]. – reference: Serfling R. 1980. Approximation theorems of mathematical statistics. New York: Wiley. – reference: Rabinowitz D, Laird N. 2000. A unified approach to adjusting association tests for population admixture with arbitrary pedigree structure and arbitrary missing marker information. Hum Hered 50:211-23. – reference: Lazzeroni L, Lange K. 2001. A conditional inference framework for extending the transmission/disequilibrium test. Hum Hered 48:67-81. – reference: Billingsley P. 1995. Probability and measure. New York: John Wiley. – reference: Lake S, Blacker D, Laird N. 2000. Family-based tests of association in the presence of linkage. Am J Hum Genet 67:1515-25. – reference: Sham P. 1997. Statistics in human genetics. Arnold. – reference: Risch N. 2000. Searching for genetic determinants in the new millennium. Nature 405:847-56. – reference: Falconer DS, Mackay TFC. 1997. Introduction to quantitative genetics. Longman. – reference: Lange C, Laird NM. 2002. Power calculations for a general class of family-based association tests. AJHG [In press]. – reference: McGinnis R. 2000. General equations for pt, ps, and the power of the tdt and the affected sib-pair test. Am J Hum Genet 67:1340-7. – reference: Allison DB, Heo M, Kaplan N, Martin ER. 1999. Sibling-based tests of linkage and association for quantitive traits. Am J Hum Genet 64:1754-64. – reference: Whittemore A, Tu I. 2000, Detection of disease genes by use of family data. Likelihood-based theory. Am J Hum Genet 66:1328-40. – reference: Laird N, Horvath S, Xu X. 2000. Implementing a unified approach to family based tests of association. Genet Epidemiol [Suppl] 19:36-42. – reference: Petrov V. 1995. Sums of independent random variables. Berlin: Springer. – reference: Rabinowitz D. 1997. A transmission disequilibrium test for quantitative trait loci. 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| Snippet | Family‐based association tests (FBATs) provide simple and powerful tests to detect association between a genetic marker and a disease‐susceptibility locus,... Family-based association tests (FBATs) provide simple and powerful tests to detect association between a genetic marker and a disease-susceptibility locus,... |
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| SubjectTerms | Asthma - genetics asymptotic distribution Biological and medical sciences conditional power FBATs Fundamental and applied biological sciences. Psychology Genetic Linkage Genetics of eukaryotes. Biological and molecular evolution Genotype Human Humans Linkage Disequilibrium Models, Genetic Nuclear Family optimal offset choices Phenotype Population genetics, reproduction patterns |
| Title | On a general class of conditional tests for family-based association studies in genetics: the asymptotic distribution, the conditional power, and optimality considerations |
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