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A General Test of Association for Quantitative Traits in Nuclear Families
Open accessAbstract
High-resolution mapping is an important step in the identification of complex disease genes. In outbred populations, linkage disequilibrium is expected to operate over short distances and could provide a powerful fine-mapping tool. Here we build on recently developed methods for linkage-disequilibrium mapping of quantitative traits to construct a general approach that can accommodate nuclear families of any size, with or without parental information. Variance components are used to construct a test that utilizes information from all available offspring but that is not biased in the presence of linkage or familiality. A permutation test is described for situations in which maximum-likelihood estimates of the variance components are biased. Simulation studies are used to investigate power and error rates of this approach and to highlight situations in which violations of multivariate normality assumptions warrant the permutation test. The relationship between power and the level of linkage disequilibrium for this test suggests that the method is well suited to the analysis of dense maps. The relationship between power and family structure is investigated, and these results are applicable to study design in complex disease, especially for late-onset conditions for which parents are usually not available. When parental genotypes are available, power does not depend greatly on the number of offspring in each family. Power decreases when parental genotypes are not available, but the loss in power is negligible when four or more offspring per family are genotyped. Finally, it is shown that, when siblings are available, the total number of genotypes required in order to achieve comparable power is smaller if parents are not genotyped.
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“Within-family genetic association estimates, such as those obtained from samples of siblings, can provide less biased estimates of direct genetic effects because they are unlikely to be affected by demographic and indirect genetic effects of parents7,17,30–34.”
From Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects (2022) · cites this paper as [31]
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Cites
Introduction to Quantitative Genetics.
Edwards, A. W. F., & Falconer, D. S. (1982) · Biometrics · doi:10.2307/2529912 · Cited by 21,447
The Future of Genetic Studies of Complex Human Diseases
Risch, N., & Merikangas, K. (1996) · Science · doi:10.1126/science.273.5281.1516 · Cited by 5,355
Spielman, R. S., McGinnis, R. E., & Ewens, W. J. (1993) · PubMed · Cited by 3,679
Wiley Series in Probability and Mathematics Statistics
Huber, P. J. (1981) · Wiley series in probability and statistics · doi:10.1002/0471725250.scard · Cited by 2,257
Searle, S. R., Casella, G., & McCulloch, C. E. (1992) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316856 · Cited by 1,926
The investigation of linkage between a quantitative trait and a marker locus
Haseman, J. K., & Elston, R. C. (1972) · Behavior Genetics · doi:10.1007/bf01066731 · Cited by 1,367
Variations on a Theme: Cataloging Human DNA Sequence Variation
Collins, F. S., Guyer, M. S., & Chakravarti, A. (1997) · Science · doi:10.1126/science.278.5343.1580 · Cited by 1,062
Introduction to Quantitative Genetics
P.B., S. (1963) · Poultry Science · doi:10.3382/ps.0420547 · Cited by 1,053
THE EVOLUTIONARY DYNAMICS OF COMPLEX POLYMORPHISMS,,
Lewontin, R. C., & Kojima, K. (1960) · Evolution · doi:10.1111/j.1558-5646.1960.tb03113.x · Cited by 769
Lander, E. S. (1999) · Nature Genetics · doi:10.1038/4427 · Cited by 556
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Franceschini, N., Tao, R., Liu, L., Rutherford, S., Haack, K., Almasy, L. A., Göring, H. H. H., Laston, S., Lee, E. T., Best, L. G., et al. (2014) · BMC Cardiovascular Disorders · doi:10.1186/1471-2261-14-158 · Cited by 5
“Therefore, we tested for the evidence of population stratification for each variant using the quantitative transmission disequilibrium test (QTDT) [37] and a test for stratification described by Havill et al. [38], both implemented in SOLAR.”
MethodInfluentialCalculation of IBD probabilities with dense SNP or sequence data
Keith, J. M., McRae, A. F., Duffy, D. L., Mengersen, K. L., & Visscher, P. M. (2008) · Genetic Epidemiology · doi:10.1002/gepi.20324 · Cited by 5
“IBD probabilities are also required for certain family-based tests of linkage disequilibrium (LD), such as those implemented in the QTDT package [Abecasis et al., 2000a,b].”
MethodOptimal Two-Stage Testing for Family-Based Genome-wide Association Studies
MacGregor, S. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.02.003 · Cited by 5
Hsu, F., Liang, K., Beaty, T. H., & Barnes, K. C. (2002) · Genetic Epidemiology · doi:10.1002/gepi.0194 · Cited by 5
“Sample Size Comparison With Method of Abecasis et al. [2000a,b] Abecasis et al. [2000a,b] developed a method called the quantitative transmission/disequilibrium test (QTDT), which currently is widely used. Recently, Abecasis et al. [2001] examined the power to detect LD with genes controlling quantitative traits under…”
BackgroundMethodResultInfluentialAnalytical Methods Applied to Psychiatric Genetics
Grigorenko, E. L., & Pauls, D. L. (2003) · Humana Press eBooks · doi:10.1385/1-59259-348-8:23 · Cited by 5
Genome‐Wide Association Studies for Next‐Generation Crop Breeding in the Postgenomic Era
Sidhu, N. S., Ganesh, P., Sowmya, M. S., Kavya, M., Krishnappa, G., & Pathy, T. L. (2025) · Plant Breeding · doi:10.1111/pbr.70017 · Cited by 4
Simianer, H., & Pimentel, E. C. G. (2009) · Journal of Animal Breeding and Genetics · doi:10.1111/j.1439-0388.2009.00812.x · Cited by 4
“The basic principle of the TDT has been extended to various more general cases like the use of haplotypes (Clayton 1999), general pedigrees (Rabinowitz & Laird 2000) or analysis of quantitative traits (Abecasis et al. 2000), the latter termed as quantitative TDT (QTDT).”
BackgroundSURFBAT: a surrogate family based association test building on large imputation reference panels
Herzig, A. F., Rubinacci, S., Marenne, G., Perdry, H., Génin, E., Campion, D., Dartigues, J., Deleuze, J., Lambert, J., Redon, R., et al. (2024) · G3 Genes Genomes Genetics · doi:10.1093/g3journal/jkae287 · Cited by 4
“With these four dosages, and depending on the context of the study sample, there is hence the possibility to apply other statistical approaches derived for family based data; notably including those that generalize the TDT framework for quantitative traits (Spielman and Ewens 1998; Abecasis et al .”
Nethononda, R. M., McGurk, K. A., Whitworth, P., Francis, J. M., Mamasoula, C., Cordell, H. J., Neubauer, S., Keavney, B. D., Mayosi, B. M., Farrall, M., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-49961-w · Cited by 4
Notes on Three Decades of Methodology Workshops
MAES, H. H. M. (2021) · Behavior Genetics · doi:10.1007/s10519-021-10049-9 · Cited by 4
Family-based association tests for rare variants with censored traits
Qi, W., Allen, A. S., & Li, Y. (2019) · PLoS ONE · doi:10.1371/journal.pone.0210870 · Cited by 4
Genetics of Susceptibility and Resistance to Infection
Cobat, A., Orlova, M., Alcaïs, A., & Schurr, E. (2010) · Methods in microbiology · doi:10.1016/s0580-9517(10)37004-8 · Cited by 5
Rice, T., Sung, Y. J., Shi, G., Gu, C. C., & Rao, D. C. (2009) · BMC Proceedings · doi:10.1186/1753-6561-3-s7-s52 · Cited by 4
“Variance-components models as parameterized in the computer programs QTDT [8] and Merlin [9] were used to perform heritability and association analyses.”
MethodVariance Components and Related Methods for Mapping Quantitative Trait Loci
Cherny, S. S. (2008) · Sociological Methods & Research · doi:10.1177/0049124108324524 · Cited by 4
“Using the imputation procedure, by genotyping a subset (usually parents and one offspring) of the members of a given family using the dense marker panel, they could infer the genotypes of the other members who were typed using only the coarse marker map, a procedure implemented in the Merlin package (Abecasis et al. 2…”
BackgroundMethodInfluentialMirea, L., Sun, L., Stafford, J. E., & Bull, S. B. (2010) · Genetic Epidemiology · doi:10.1002/gepi.20506 · Cited by 4
“Testing for equality between the IA and FA estimates corresponds to a test for PSB, as described and implemented in the accompanying software package QTDT [Abecasis et al., 2000].”
BackgroundMethodInfluentialTesting for association in genetic studies
Laird, N. M., Kraft, P. L., Lange, C., & Steen, K. V. (2005) · CRC Press eBooks · doi:10.1201/b13341-5 · Cited by 4
Markey, A. (2013) · Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · Cited by 4
Comparison of the QTDT Analysis for IgE in the CSGA Data Set
Page, G. P., Wilcox, M., Occhiuto, J., Adak, S., Neuberg, D. S., Bajorunaite, R., & George, V. T. (2001) · Genetic Epidemiology · doi:10.1002/gepi.2001.21.s1.s312 · Cited by 4
Ghosh, S., Sanapala, K. R., Ghosh, A., & Chakladar, S. (2009) · BMC Proceedings · doi:10.1186/1753-6561-3-s7-s18 · Cited by 4
“While some family-based methods of association have been developed for quantitative traits [1-3], population-based quantitative trait data have usually been analyzed using classical analysis of variance (ANOVA) methods.”
Linkage and Association: The Transmission/Disequilibrium Test for QTLs
Iles, M. M. (2003) · Humana Press eBooks · doi:10.1385/1-59259-176-0:101 · Cited by 4
The Genetics of Osteoporosis: Future Diagnostic Possibilities
Brown, M. A., & Eisman, J. A. (2000) · Clinics in Laboratory Medicine · doi:10.1016/s0272-2712(18)30051-9 · Cited by 4
Transmission/Disequilibrium Test
Seillier‐Moiseiwitsch, F., & Niu, T. (2014) · Wiley StatsRef: Statistics Reference Online · doi:10.1002/9781118445112.stat07645 · Cited by 4
Fan, R., Floros, J., & Xiong, M. (2002) · Human Heredity · doi:10.1159/000064975 · Cited by 4
Critical Issues in Genetic Association Studies
Prom‐Wormley, E. C., Adkins, A. E., Waldman, I. D., & Dick, D. M. (2017) · Wiley eBooks · doi:10.1002/9781119095910.ch12 · Cited by 4
Genetic Mapping of Quantitative Trait Loci for Disease-Related Phenotypes
Devoto, M., & Falchi, M. (2012) · Methods in molecular biology · doi:10.1007/978-1-61779-785-9_15 · Cited by 3
QTL Methodology in Behavior Genetics
Cherny, S. S. (2009) · Springer eBooks · doi:10.1007/978-0-387-76727-7_3 · Cited by 3
Veddum, L., Greve, A. N., Gregersen, M., Andreassen, A. K., Knudsen, C. B., Brandt, J. M., Krantz, M. F., Søndergaard, A., Burton, B. K., Jepsen, J. R. M., et al. (2023) · Psychiatry Research · doi:10.1016/j.psychres.2023.115280 · Cited by 3
“1 (Abecasis et al., 2000) to estimate the variance components of the social responsiveness phenotype using SRS-2 outcomes for children (teacher or primary caregiver ratings) and parents (self-report).”
Innate Immunity Genes as Candidate Genes
Rihet, P. (2008) · Humana Press eBooks · doi:10.1007/978-1-59745-570-1_2 · Cited by 3
Jiang, Y., Ji, Y., Sibley, A. B., Li, Y., & Allen, A. S. (2016) · Genetic Epidemiology · doi:10.1002/gepi.22022 · Cited by 3
“As Abecasis et al proposed (Abecasis et al., 2000), the between family component will be the average of sibling’s genotype, i.”
BackgroundMethodTwin studies in inherited eye disease
Nag, A., & Hammond, C. J. (2013) · Clinical and Experimental Ophthalmology · doi:10.1111/ceo.12233 · Cited by 3
Alcaïs, A., & Abel, L. (2003) · Genetic Epidemiology · doi:10.1002/gepi.10220 · Cited by 3
“…can be classified as nonparametric [e.g., Monks and Kaplan, 2000] while others rely either on regression [e.g., Allison et al., 1999; Waldman et al., 1999; Sun et al., 2000; George et al., 1999] or variance-component [e.g., Fulker et al., 1999; Sham et al., 2000; Abecasis et al., 2000] techniques.”
MethodInfluentialAssociation testing to detect gene–gene interactions on sex chromosomes in trio data
Lee, Y., Ghosh, D., & Zhang, Y. (2013) · Frontiers in Genetics · doi:10.3389/fgene.2013.00239 · Cited by 3
“It has been known that population stratification can result in spurious association findings in mixed effects model settings (Abecasis et al., 2000).”
BackgroundInfluentialKnight, S., Uh, H., & Martinez, M. M. (2009) · Genetic Epidemiology · doi:10.1002/gepi.20480 · Cited by 3
Linkage and Association Analyses of Longitudinally Measured Lipid Phenotypes in Adolescence
Middelberg, R. P. S., Gordon, S. D., Zhu, G., McRae, A. F., Montgomery, G. W., Martin, N. G., & Whitfield, J. B. (2008) · Twin Research and Human Genetics · doi:10.1375/twin.11.6.603 · Cited by 3
“To test for the presence of stratification, a comparision of the likelihood of a model with all parameters free versus a model where βw = βB was fitted (Fulker & Cherny, 1996; Fulker et al., 1999; Abecasis et al., 2000).”
MethodHill, L. D., Ewens, K. G., Maher, B. S., York, T. P., Legro, R. S., Dunaif, A. E., & Strauss, J. F. (2011) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2011.11.022 · Cited by 3
“edu/csg/abecasis/QTDT/) (Abecasis et al., 2000) in the family study.”
MethodEMK: A Novel Program for Family‐Based Allelic and Genotypic Association Tests on Quantitative Traits
Li, Y. W., Martin, E. R., & Li, Y. (2008) · Annals of Human Genetics · doi:10.1111/j.1469-1809.2008.00432.x · Cited by 3
“In particular, the QTDT implements five association methods (Abecasis et al. 2000; Allison 1997; Rabinowitz 1997; Monks & Kaplan 2000; Fulker et al. 1999), in which the likelihood-based orthogonal model (OM) (Abecasis et al. 2000) and the TDT-based Monks and Kaplan (MK) method (Monks & Kaplan 2000)…”
MethodPerspectives on genome‐wide multi‐stage family‐based association studies
Steen, K. V. (2011) · Statistics in Medicine · doi:10.1002/sim.4259 · Cited by 3
A Variance-Component Framework for Pedigree Analysis of Continuous and Categorical Outcomes
Epstein, M. P., Hunter, J. E., Allen, E. G., Sherman, S. L., Lin, X., & Boehnke, M. (2009) · Statistics in Biosciences · doi:10.1007/s12561-009-9010-5 · Cited by 3
“We would base this LD extension on the work of Abecasis et al. [ 1 ], who extended the traditional VC framework to test for marker association at a linked gene locus for nuclear families.”
MethodThe use of genetic correlations to evaluate associations between SNP markers and quantitative traits
Brawner, J. T., Dillon, S. K., Lee, D. J., Meder, A. R., Dieters, M. J., & Southerton, S. G. (2012) · Tree Genetics & Genomes · doi:10.1007/s11295-012-0530-7 · Cited by 3
“As well, association tests in human studies often focus on family-based association tests that utilize within-family differences to avoid bias from population structure or cryptic relationships (Fulker et al. 1999; Abecasis et al. 2000).”
BackgroundThe ordered transmission disequilibrium test: detection of modifier genes
Perdry, H., Babron, M., & Clerget‐Darpoux, F. (2008) · Genetic Epidemiology · doi:10.1002/gepi.20348 · Cited by 3
“An alternative way to take into account a DRCV in a TDT is to use a simple linear model, assuming that the DRCV is normally distributed, with a variance independent of the genotype; this can be done as a special case of the quantitative transmission disequilibrium test (QTDT) described by Abecasis et al. [2000a,b], wh…”
Methodcophesim: A comprehensive phenotype simulator for testing novel association methods
Zhbannikov, I. Y., Arbeev, K. G., & Yashin, A. I. (2017) · F1000Research · doi:10.12688/f1000research.11968.1 · Cited by 3
Investigation of parent-of-origin effects induced by fenofibrate treatment on triglycerides levels
Sarnowski, C., Lent, S., & Dupuis, J. (2018) · BMC Genetics · doi:10.1186/s12863-018-0640-9 · Cited by 3
The Boulder Workshop Question Box
Evans, D. M. (2020) · Behavior Genetics · doi:10.1007/s10519-020-10022-y · Cited by 3
Dissection of Agronomic Traits in Crops by Association Mapping
Chen, Y. (2013) · Springer eBooks · doi:10.1007/978-94-007-5687-8_6 · Cited by 3
The hyperserotonemia of autism spectrum disorders
Mulder, E. J. (2006) · University of Groningen research database (University of Groningen / Centre for Information Technology) · Cited by 3
Family-Based Association Analysis
McCarthy, M. I., & Wiltshire, S. (2004) · Dictionary of Bioinformatics and Computational Biology · doi:10.1002/0471650129.dob0232 · Cited by 3
Molecular Genetics of Schizophrenia and Related Intermediate Phenotypes in a Founder Population
Wedenoja, J. (2010) · Työväentutkimus Vuosikirja · Cited by 3
Using linkage and association to identify and model genetic effects: summary of GAW15 Group 4
Yang, Q., Biernacka, J. M., Chen, M., Houwing‐Duistermaat, J. J., Bergemann, T. L., Basu, S., Fan, R., Liu, L., Bourgey, M., Clerget‐Darpoux, F., et al. (2007) · Genetic Epidemiology · doi:10.1002/gepi.20278 · Cited by 3
Visualizing genotype × phenotype relationships in the GAW15 simulated data
Qin, X., Schmidt, S., Martin, E. R., & Hauser, E. R. (2007) · BMC Proceedings · doi:10.1186/1753-6561-1-s1-s132 · Cited by 3
“To evaluate our qualitative conclusions, we performed quantitative trait association analysis using the Monks-Kaplan method [3] as implemented in the QTDT program [4].”
Evidence for a quantitative trait locus for plasma fibrinogen from a family–based association study
Mayosi, B. M., Vickers, M. A., Green, F. R., Ratcliffe, P. J., Julier, C., Lathrop, M. G., Watkins, H. C., & Keavney, B. D. (2001) · GeneScreen · doi:10.1046/j.1466-920x.2001.00037.x · Cited by 3
Mathematics-assisted mapping in analysis of medical disease
Sillanpää, M. J. (2002) · Annals of Medicine · doi:10.1080/078538902320322556 · Cited by 3
Resolving the heterogeneity of psychiatric disorders: Clinical and statistical approaches
Zandi, P. P., & DePaulo, J. R. (2005) · Clinical Neuroscience Research · doi:10.1016/j.cnr.2005.07.006 · Cited by 3
Rowe Suzanne, J. (2008) · Cited by 3
Michelle Luciano, A., Hine, E., Wright, M. J., Duffy, D. L., MacMillan, J., & Martin, N. G. (2006) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.30413 · Cited by 3
“While association of DRPLA and inspection time was supported in the QTDT analyses (P¼ 0.01), this result may be less reliable than that from Mx where unequal variances between males and females were explicitly modeled.”
MethodInfluentialAnalysis of Quantitative Trait Loci
Falchi, M. (2008) · Methods in molecular biology · doi:10.1007/978-1-60327-429-6_16 · Cited by 3
Genetic prediction of complex traits: integrating infinitesimal and marked genetic effects
Carré, C., Gamboa, F., Cros, D., Hickey, J. M., Gorjanc, G., & Manfredi, E. (2013) · Genetica · doi:10.1007/s10709-013-9722-9 · Cited by 2
“…models included genetic transmission at unobserved segregating QTL (e.g., Fernando and Grossman 1989; Meuwissen and Goddard 2000; Legarra and Fernando 2009) and combined within family and between family marker effects in the context of methodology for QTL search (e.g., Abecasis et al. 2000).”
BackgroundThe Sorghum Genome: Current Status and Future Prospects
Rajendrakumar, P. (2020) · Springer eBooks · doi:10.1007/978-981-15-8249-3_20 · Cited by 2
Genetic association tests based on ranks (GATOR) for quantitative traits with and without censoring
Allen, A. S., Martin, E. R., Qin, X., & Li, Y. (2006) · Genetic Epidemiology · doi:10.1002/gepi.20141 · Cited by 2
“Li and Fan [2000] proposed a method based on the Cox model that combines the hazard function with the orthogonal model [Abecasis et al., 2000] to test for association between a marker and disease by incorporating AAO or censoring time in the test statistic.”
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Li, D., Zhou, J. J., Thomas, D. C., & Fardo, D. W. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21822 · Cited by 2
“…strategies in the common variants era, that is, the traditional transmissionbased tests such as FBAT and the transmission disequilibrium test (TDT) [Abecasis et al., 2000; Allison, 1997; Cleves et al., 1997; Laird et al., 2000; Spielman et al., 1993] and the recently developed variance-components…”
MethodInfluentialPowerful tests for association on quantitative trait loci incorporating imprinting effects
Xia, F., Zhou, J., & Fung, W. K. (2013) · Journal of Human Genetics · doi:10.1038/jhg.2013.22 · Cited by 2
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Lee, H., Kim, M., & Park, M. (2010) · Korean Journal of Applied Statistics · doi:10.5351/kjas.2010.23.1.095 · Cited by 2
Haldar, T., Mukhopadhyay, I., & Ghosh, S. (2014) · BMC Proceedings · doi:10.1186/1753-6561-8-s1-s71 · Cited by 2
“Although transmission-based tests for association of both binary and quantitative traits have been extensively studied [1-4], extension of such tests for multivariate phenotypes is of current research interest.”
BackgroundA Powerful Nonparametric Statistical Framework for Family-Based Association Analyses
Li, M., He, Z., Schaid, D. J., Cleves, M. A., Nick, T. G., & Lu, Q. L. (2015) · Genetics · doi:10.1534/genetics.115.175174 · Cited by 2
“Simulations with population strati fi cation: The second simulation was conducted to evaluate the performance of the family-U statistics and FBAT in the presence of PS.”
MethodInfluential(iii) Whole-genome association studies of complex diseases
Sham, P. C., Cherny, S. S., Kao, P. Y. P., Song, Y., Chan, D. T.-M., & Cheung, K. (2008) · Current Orthopaedics · doi:10.1016/j.cuor.2008.05.006 · Cited by 2
A Family‐Based Robust Multivariate Association Test Using Maximum Statistic
Hsieh, T.-J., Chang, S. H., & Tai, J. J. (2014) · Annals of Human Genetics · doi:10.1111/ahg.12054 · Cited by 2
“…loci (QTLs) can be detected via investigation of the association between a quantitative trait and a marker locus (Allison, 1997; Rabinowitz, 1997; Abecasis et al., 2000; Monks & Kaplan, 2000; Kistner & Weinberg, 2004; Wheeler ∗Corresponding author: Dr. John Jen Tai, Department of Statistics and…”
BackgroundStatistical issues and approaches in endophenotype research
Sham, P. C., Cherny, S. S., & Hall, M. (2011) · Chinese Science Bulletin · doi:10.1007/s11434-011-4746-y · Cited by 2
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Melroy-Greif, W. E., Vadász, C., Kamens, H. M., McQueen, M. B., Corley, R. P., Stallings, M. C., Hopfer, C. J., Krauter, K. S., Brown, S. A., Hewitt, J. K., et al. (2016) · Alcohol · doi:10.1016/j.alcohol.2015.10.005 · Cited by 2
2015 ASHG Awards and Addresses
(2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.01.013 · Cited by 2
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Kulkarni, H., & Ghosh, S. (2017) · Journal of Human Genetics · doi:10.1038/jhg.2017.9 · Cited by 2
Bani‐Fatemi, A., Howe, A. S., Zai, C. C. H., Kennedy, J. L., Vincent, J. B., Strauss, J., Wong, A. H. C., & Luca, V. D. (2016) · Neuropsychobiology · doi:10.1159/000456010 · Cited by 2
Fuady, A. M., Lent, S., Sarnowski, C., & Tintle, N. (2018) · BMC Genetics · doi:10.1186/s12863-018-0647-2 · Cited by 2
“used the linear mixed effect model provided by the QTDT software [12] to perform parent-of-origin effect association analyses with TG levels at baseline, follow-up, or on the difference between baseline and follow-up.”
MethodInfluentialStatus and Prospectives of Genome-Wide Association Studies in Plants
Dash, G. K., Sabarinathan, S., Donde, R., Gouda, G., Gupta, M. K., Behera, L., & Swain, P. (2021) · Springer eBooks · doi:10.1007/978-981-16-3993-7_19 · Cited by 3
Family-Based Association Studies
Zhang, K., & Zhao, H. (2009) · Springer eBooks · doi:10.1007/978-3-540-69264-5_7 · Cited by 2
McGurk, K. A., Farrell, L. N., Kendall, A. C., Keavney, B. D., & Nicolaou, A. (2022) · Prostaglandins & Other Lipid Mediators · doi:10.1016/j.prostaglandins.2022.106638 · Cited by 2
Cretin, J., Adjemout, M., Dieppois, C., Gallardo, F., Torres, M., Merard, Z., Sawadogo, S. A., Picard, C., Rihet, P., & Paul, P. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms242115711 · Cited by 2
Huang, Q.-Y., Shen, H., Deng, H.-Y., Conway, T., Elze, L., Davies, K. M., Recker, R. R., & Deng, H. (2006) · Journal of Bone and Mineral Metabolism · doi:10.1007/s00774-005-0659-7 · Cited by 2
Wang, Y., Yang, Q., & Rabinowitz, D. (2010) · Biometrics · doi:10.1111/j.1541-0420.2010.01454.x · Cited by 2
“, 1999; Abecasis et al., 2000) in which case the weighted least squares method is more efficient. The efficiency gains of the weighted least squares increased with the severity of admixture. When the difference between the intercepts of the two populations was 15, the reduction of the empirical standard error of the e…”
BackgroundMethodResultInfluentialGENETIC SUSCEPTIBILITY TO THE METABOLIC SYNDROME
Bossé, Y. (2004) · Corpus Université Laval (Université Laval) · Cited by 2
Quantitative Trait Loci Mapping
Xiong, D.-H., Liu, J., Guo, Y.-F., Guo, Y., Yang, T., Jiang, H., Chen, Y., Yang, F., Recker, R. R., & Deng, H. (2008) · Methods in molecular biology · doi:10.1007/978-1-59745-104-8_16 · Cited by 3
Localization and Identification of Genes Affecting Language and Learning
Smith, S. D. (2004) · Psychology Press eBooks · doi:10.4324/9781410610881-20 · Cited by 2
Family‐based Association Test ( FBAT )
Laird, N. M. (2011) · Encyclopedia of Life Sciences · doi:10.1002/9780470015902.a0022500 · Cited by 2
Direct effect of genetic ancestry on complex traits in a Mexican populationPreprint
Wang, S., Berumen-Campos, J., Vergara-Lope, A., Baca, P., Barrera, E., Rivas, F., Aguilar-Ramirez, D. J., Collins, R., Emberson, J., Hill, M., et al. (2025) · medRxiv · doi:10.1101/2025.09.09.25335237 · Cited by 2
GENETICS | Gene Association Studies
Litonjua, A. A., & Celedon, J. C. (2006) · Elsevier eBooks · doi:10.1016/b0-12-370879-6/00165-4 · Cited by 2
Identifying Causal Genotype–Phenotype Relationships for Population‐Sampled Parent–Child Trios
Tang, Y., Cabreros, I., & Storey, J. D. (2026) · Genetic Epidemiology · doi:10.1002/gepi.70027 · Cited by 1
“We contrasted the TMT to family‐based association methods including the family‐based association test (FBAT) (Laird et al. 2000), the quantitative TDT (QTDT) (Abecasis et al. 2000) and the family‐based GWAS (FGWAS) (Young et al. 2022).”
InfluentialWithin-family effect of ancestry on complex traits in a Mexican population
Wang, S., Berumen-Campos, J., Vergara-Lope, A., Baca, P., Barrera, E., Rivas, F., Aguilar-Ramirez, D. J., Collins, R., Emberson, J., Hill, M., et al. (2026) · Nature · doi:10.1038/s41586-026-11039-9 · Cited by 2
Association Analysis in Family Designs
Laird, N. M., & Lange, C. (2010) · Statistics for biology and health · doi:10.1007/978-1-4419-7338-2_9 · Cited by 1
Cwynar, M., Wojciechowska, W., Stolarz, K., Wizner, B., Kawecka−Jaszcz, K., Staessen, J. A., & Grodzicki, T. K. (2006) · Arterial Hypertension · Cited by 1
Detecting genes contributing to longevity using twin data
Begun, A. (2009) · Human Genomics · doi:10.1186/1479-7364-4-2-73 · Cited by 1
“Another solution for this problem is to partition the association effects into between- and within-family components.(13,14) It was shown that admixture impacts the between-family component estimate, and that the within-family component estimate is independent of any ‘spurious’ effects when samples from a number of po…”
BackgroundRoine, U., Ripatti, S., Rehnström, K., Roine, T., Kilpinen, H., Surakka, I., Wedenoja, J., Ylisaukko‐oja, T., Kempas, E. I., Wessman, J., et al. (2013) · Autism - Open Access · doi:10.4172/2165-7890.1000107 · Cited by 1
Likelihood Ratio Test of Hardy-Weinberg Equilibrium Using Uncertain Genotypes for Sibship Data
(2014) · International Journal of Biomedical Data Mining · doi:10.4172/2090-4924.1000104 · Cited by 1
Statistical Analysis of Genome-wide Association Studies for Myopia
Li, Y., & Fan, Q. (2010) · WORLD SCIENTIFIC eBooks · doi:10.1142/9789812832986_0013 · Cited by 1
Clinical Genetics for the Dental Practitioner
Hartsfield, J. K., & Bixler, D. (2010) · Elsevier eBooks · doi:10.1016/b978-0-323-05724-0.50010-2 · Cited by 1
Darst, B. F., & Engelman, C. D. (2016) · BMC Proceedings · doi:10.1186/s12919-016-0031-z · Cited by 1
“Recently, a new method was developed that addresses both of these issues by integrating the QTDT (quantitative transmission disequilibrium test) framework [21] into the kernel based model, KMFAM [22].”
MethodRobust Rare-Variant Association Tests for Quantitative Traits in General Pedigrees
Jiang, Y., Conneely, K. N., & Epstein, M. P. (2017) · Statistics in Biosciences · doi:10.1007/s12561-017-9197-9 · Cited by 1
“The QTDT framework [1] for general pedigrees decomposes a genotype into a between-family component (which is sensitive to population stratification) and a within-family component (which is robust to population stratification).”
BackgroundMethodInfluentialLou, X., Hou, T., Liu, S., Xu, H., Lin, F., Tang, X., MacLeod, S. L., Cleves, M. A., & Hobbs, C. A. (2020) · Genetic Epidemiology · doi:10.1002/gepi.22363 · Cited by 1
“…fetal and maternal genetic effects (Mitchell, 1997); for genomic imprinting and hybrid family designs (Hu & Zhou, 2010; Hu et al., 2007; Hu, Zhou, Sun et al., 2007); and for quantitative traits (Abecasis et al., 2000; Allison, 1997; Monks & Kaplan, 2000; Rabinowitz, 1997; Xiong et al., 1998).”
BackgroundSingle Marker Family-Based Association Analysis Conditional on Parental Information
Chung, R., Kinnamon, D. D., & Martin, E. R. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-7274-6_19 · Cited by 1
Family-based Association Methods
Lasky-Su, J. A., Murphy, A., Won, S., & Lange, C. (2010) · Elsevier eBooks · doi:10.1016/b978-0-12-375142-3.10014-8 · Cited by 1
Adaptive robust genetic association tests using case‐parents triad families
Wang, J., & Tai, J. (2015) · Biometrical journal. Biometrische Zeitschrift · doi:10.1002/bimj.201300135 · Cited by 1
“…real studies for identification of disease susceptibility genes (Sham and Curtis, 1995; Allison, 1997; Kaplan et al., 1997; Spielman and Ewens, 1998; Clayton and Jones, 1999; Weinberg, 1999; Abecasis et al., 2000; Gordon et al., 2001; Shuang et al., 2004; Malik et al., 2005; Dubinsky et al., 2007).”
Background
Metadata
- Authors
- Abecasis, G. R., Cardon, L. R., & Cookson, W. O. C.
- Affiliations
- Centre for Human Genetics (GB)
- Corresponding author
- Abecasis, G.R.
- ORCID
- Abecasis, G.R.
- Venue
- The American Journal of Human Genetics
- Publisher
- Elsevier BV
- Published
- 2000-01
- Volume
- 66
- Issue
- 1
- Pages
- 279-292
- ISSN
- 0002-9297 (ISSN-L)
- PMC
- PMC1288332
- OpenAlex
- W2078625752
- Cited by
- 1,126
- References
- 30
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 7 · 2023: 7 · 2022: 6 · 2021: 13 · 2020: 15 · 2019: 13 · 2018: 18 · 2017: 23 · 2016: 22 · 2015: 26 · 2014: 27 · 2013: 38 · 2012: 51
- FWCI
- 27.12
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- The American Journal of Human Genetics (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Wellcome Trust
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Keywords
- association mapping, quantitative traits, nuclear family, variance components, permutation tests, fine mapping, power analysis, family structure, parental genotypes, multivariate normality, research design
- MeSH terms
- Genetics, Population, Humans, Models, Genetic, Nuclear Family, Linkage Disequilibrium, Quantitative Trait, Heritable
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