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Haplotype association analysis of discrete and continuous traits using mixture of regression models

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Haplotype association analysis of discrete and continuous traits using mixture of regression models. / Sham, Pak C.; Rijsdijk, F. V.; Knight, Jo et al.
In: Behavior Genetics, Vol. 34, No. 2, 03.2004, p. 207-214.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Sham, PC, Rijsdijk, FV, Knight, J, Makoff, A, North, B & Curtis, D 2004, 'Haplotype association analysis of discrete and continuous traits using mixture of regression models', Behavior Genetics, vol. 34, no. 2, pp. 207-214. https://doi.org/10.1023/B:BEGE.0000013734.39266.a3

APA

Sham, P. C., Rijsdijk, F. V., Knight, J., Makoff, A., North, B., & Curtis, D. (2004). Haplotype association analysis of discrete and continuous traits using mixture of regression models. Behavior Genetics, 34(2), 207-214. https://doi.org/10.1023/B:BEGE.0000013734.39266.a3

Vancouver

Sham PC, Rijsdijk FV, Knight J, Makoff A, North B, Curtis D. Haplotype association analysis of discrete and continuous traits using mixture of regression models. Behavior Genetics. 2004 Mar;34(2):207-214. doi: 10.1023/B:BEGE.0000013734.39266.a3

Author

Sham, Pak C. ; Rijsdijk, F. V. ; Knight, Jo et al. / Haplotype association analysis of discrete and continuous traits using mixture of regression models. In: Behavior Genetics. 2004 ; Vol. 34, No. 2. pp. 207-214.

Bibtex

@article{334503873ba84186940637b182578da3,
title = "Haplotype association analysis of discrete and continuous traits using mixture of regression models",
abstract = "We present a regression-based method of haplotype association analysis for quantitative and dichotomous traits in samples consisting of unrelated individuals. The method takes account of uncertain phase by initially estimating haplotype frequencies and obtaining the posterior probabilities of all possible haplotype combinations in each individual, then using these as weights in a finite mixture of regression models. Using this method, different combinations of marker loci can be modeled, to find a parsimonious set of marker loci that are most predictive and therefore most likely to be closely associated with the a quantitative trait locus. The method has the additional advantage of being able to use individuals with some missing genotype data, by considering all possible genotypes at the missing markers. We have implemented this method using the SNPHAP and Mx programs and illustrated its use on published data on idiopathic generalized epilepsy.",
keywords = "Chromosome Mapping, Epilepsy, Generalized, Gene Frequency, Genetic Markers, Genetics, Population, Genotype, Haplotypes, Humans, Logistic Models, Mathematical Computing, Models, Genetic, Models, Statistical, Phenotype, Probability, Quantitative Trait Loci, Software",
author = "Sham, {Pak C.} and Rijsdijk, {F. V.} and Jo Knight and Andrew Makoff and B. North and D. Curtis",
year = "2004",
month = mar,
doi = "10.1023/B:BEGE.0000013734.39266.a3",
language = "English",
volume = "34",
pages = "207--214",
journal = "Behavior Genetics",
issn = "0001-8244",
publisher = "Springer New York",
number = "2",

}

RIS

TY - JOUR

T1 - Haplotype association analysis of discrete and continuous traits using mixture of regression models

AU - Sham, Pak C.

AU - Rijsdijk, F. V.

AU - Knight, Jo

AU - Makoff, Andrew

AU - North, B.

AU - Curtis, D.

PY - 2004/3

Y1 - 2004/3

N2 - We present a regression-based method of haplotype association analysis for quantitative and dichotomous traits in samples consisting of unrelated individuals. The method takes account of uncertain phase by initially estimating haplotype frequencies and obtaining the posterior probabilities of all possible haplotype combinations in each individual, then using these as weights in a finite mixture of regression models. Using this method, different combinations of marker loci can be modeled, to find a parsimonious set of marker loci that are most predictive and therefore most likely to be closely associated with the a quantitative trait locus. The method has the additional advantage of being able to use individuals with some missing genotype data, by considering all possible genotypes at the missing markers. We have implemented this method using the SNPHAP and Mx programs and illustrated its use on published data on idiopathic generalized epilepsy.

AB - We present a regression-based method of haplotype association analysis for quantitative and dichotomous traits in samples consisting of unrelated individuals. The method takes account of uncertain phase by initially estimating haplotype frequencies and obtaining the posterior probabilities of all possible haplotype combinations in each individual, then using these as weights in a finite mixture of regression models. Using this method, different combinations of marker loci can be modeled, to find a parsimonious set of marker loci that are most predictive and therefore most likely to be closely associated with the a quantitative trait locus. The method has the additional advantage of being able to use individuals with some missing genotype data, by considering all possible genotypes at the missing markers. We have implemented this method using the SNPHAP and Mx programs and illustrated its use on published data on idiopathic generalized epilepsy.

KW - Chromosome Mapping

KW - Epilepsy, Generalized

KW - Gene Frequency

KW - Genetic Markers

KW - Genetics, Population

KW - Genotype

KW - Haplotypes

KW - Humans

KW - Logistic Models

KW - Mathematical Computing

KW - Models, Genetic

KW - Models, Statistical

KW - Phenotype

KW - Probability

KW - Quantitative Trait Loci

KW - Software

U2 - 10.1023/B:BEGE.0000013734.39266.a3

DO - 10.1023/B:BEGE.0000013734.39266.a3

M3 - Journal article

C2 - 14755185

VL - 34

SP - 207

EP - 214

JO - Behavior Genetics

JF - Behavior Genetics

SN - 0001-8244

IS - 2

ER -