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Statements

Subject Item
n2:RIV%2F00027014%3A_____%2F12%3A%230001576%21RIV13-MZE-00027014
rdf:type
n4:Vysledek skos:Concept
rdfs:seeAlso
http://www.agriculturejournals.cz/publicFiles/59684.pdf
dcterms:description
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 raises 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 the Bonferroni correction), while the fixed haplotype models had lower power and excessively high type I errors. 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 a similar pedigree structure. 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 raises 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 the Bonferroni correction), while the fixed haplotype models had lower power and excessively high type I errors. 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 a similar pedigree structure.
dcterms:title
Strategies for haplotype-based association mapping in a complex pedigreed population Strategies for haplotype-based association mapping in a complex pedigreed population
skos:prefLabel
Strategies for haplotype-based association mapping in a complex pedigreed population Strategies for haplotype-based association mapping in a complex pedigreed population
skos:notation
RIV/00027014:_____/12:#0001576!RIV13-MZE-00027014
n4:predkladatel
n18:ico%3A00027014
n3:aktivita
n13:P
n3:aktivity
P(QH71275), P(QH91270)
n3:cisloPeriodika
1
n3:dodaniDat
n17:2013
n3:domaciTvurceVysledku
n14:5287278
n3:druhVysledku
n15:J
n3:duvernostUdaju
n16:S
n3:entitaPredkladatele
n5:predkladatel
n3:idSjednocenehoVysledku
171599
n3:idVysledku
RIV/00027014:_____/12:#0001576
n3:jazykVysledku
n9:eng
n3:klicovaSlova
association mapping, haplotype, complex pedigree, false positives
n3:klicoveSlovo
n12:complex%20pedigree n12:haplotype n12:association%20mapping n12:false%20positives
n3:kodStatuVydavatele
CZ - Česká republika
n3:kontrolniKodProRIV
[B65DCC761BDB]
n3:nazevZdroje
Czech Journal of Animal Science
n3:obor
n19:GI
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
4
n3:projekt
n11:QH71275 n11:QH91270
n3:rokUplatneniVysledku
n17:2012
n3:svazekPeriodika
57
n3:tvurceVysledku
Bolečková, Jana Sorensen, P. Christensen, O. F. Sahana, G.
n3:wos
000300598300001
s:issn
1212-1819
s:numberOfPages
9