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Peter Sørensen

Strategies for haplotype-based association mapping in complex pedigreed populations

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Strategies for haplotype-based association mapping in complex pedigreed populations. / Boleckova, J; Christensen, Ole Fredslund; Sørensen, Peter; Sahana, Goutam.

I: Czech Journal of Animal Science, Bind 57, Nr. 1, 2012, s. 1-9.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

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Boleckova, J o.a.. "Strategies for haplotype-based association mapping in complex pedigreed populations". Czech Journal of Animal Science. 2012, 57(1). 1-9.

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Bibtex

@article{2f45ac00813111dfa7a3000ea68e967b,
title = "Strategies for haplotype-based association mapping in complex pedigreed populations",
abstract = "In association mapping, haplotype-based methods are generally regarded to provide higher power and increased precision than methods based on single markers. For haplotype-based association mapping most studies use a fixed haplotype effect in the model. However, an increase in haplotype length increases the number of parameters in the model, resulting in low accuracy of the estimates especially for the low-frequency haplotypes. Modeling of haplotype effects can be improved if they are assumed to be random effects, as only one parameter i.e. haplotype variance needs to be estimated compared to estimating the effects of all different haplotypes in a fixed haplotype model. Using simulated data, we investigated statistical models where haplotypes were fitted either as a fixed or random effect and we compared them for the power, precision, and type I error. We investigated five haplotype lengths of 2, 4, 6, 10 and 20. The simulated data resembled the Danish Holstein cattle pedigree representing a complex relationship structure and QTL effects of different sizes were simulated. We observed that the random haplotype models had high power and very low type I error rates (after Bonferroni correction), while the fixed haplotype models had lower power and excessively high type I errors. A haplotype length of 4 to 6 gave the best results for random model in the present study. Though the present study was conducted on data structure more frequent in livestock, our findings on random vs. fixed haplotype effects in association mapping models are applicable to data from other species with similar pedigree structure",
keywords = "Association mapping, haplotype, complex pedigree, false positives",
author = "J Boleckova and Christensen, {Ole Fredslund} and Peter S{\o}rensen and Goutam Sahana",
year = "2012",
language = "English",
volume = "57",
pages = "1--9",
journal = "Czech Journal of Animal Science",
issn = "1212-1819",
publisher = "Czech Academy of Agricultural Sciences",
number = "1",

}

RIS

TY - JOUR

T1 - Strategies for haplotype-based association mapping in complex pedigreed populations

AU - Boleckova, J

AU - Christensen, Ole Fredslund

AU - Sørensen, Peter

AU - Sahana, Goutam

PY - 2012

Y1 - 2012

N2 - In association mapping, haplotype-based methods are generally regarded to provide higher power and increased precision than methods based on single markers. For haplotype-based association mapping most studies use a fixed haplotype effect in the model. However, an increase in haplotype length increases the number of parameters in the model, resulting in low accuracy of the estimates especially for the low-frequency haplotypes. Modeling of haplotype effects can be improved if they are assumed to be random effects, as only one parameter i.e. haplotype variance needs to be estimated compared to estimating the effects of all different haplotypes in a fixed haplotype model. Using simulated data, we investigated statistical models where haplotypes were fitted either as a fixed or random effect and we compared them for the power, precision, and type I error. We investigated five haplotype lengths of 2, 4, 6, 10 and 20. The simulated data resembled the Danish Holstein cattle pedigree representing a complex relationship structure and QTL effects of different sizes were simulated. We observed that the random haplotype models had high power and very low type I error rates (after Bonferroni correction), while the fixed haplotype models had lower power and excessively high type I errors. A haplotype length of 4 to 6 gave the best results for random model in the present study. Though the present study was conducted on data structure more frequent in livestock, our findings on random vs. fixed haplotype effects in association mapping models are applicable to data from other species with similar pedigree structure

AB - In association mapping, haplotype-based methods are generally regarded to provide higher power and increased precision than methods based on single markers. For haplotype-based association mapping most studies use a fixed haplotype effect in the model. However, an increase in haplotype length increases the number of parameters in the model, resulting in low accuracy of the estimates especially for the low-frequency haplotypes. Modeling of haplotype effects can be improved if they are assumed to be random effects, as only one parameter i.e. haplotype variance needs to be estimated compared to estimating the effects of all different haplotypes in a fixed haplotype model. Using simulated data, we investigated statistical models where haplotypes were fitted either as a fixed or random effect and we compared them for the power, precision, and type I error. We investigated five haplotype lengths of 2, 4, 6, 10 and 20. The simulated data resembled the Danish Holstein cattle pedigree representing a complex relationship structure and QTL effects of different sizes were simulated. We observed that the random haplotype models had high power and very low type I error rates (after Bonferroni correction), while the fixed haplotype models had lower power and excessively high type I errors. A haplotype length of 4 to 6 gave the best results for random model in the present study. Though the present study was conducted on data structure more frequent in livestock, our findings on random vs. fixed haplotype effects in association mapping models are applicable to data from other species with similar pedigree structure

KW - Association mapping

KW - haplotype

KW - complex pedigree

KW - false positives

M3 - Journal article

VL - 57

SP - 1

EP - 9

JO - Czech Journal of Animal Science

JF - Czech Journal of Animal Science

SN - 1212-1819

IS - 1

ER -