Genetic Epidemiology, Psychiatric Genetics, Asthma Genetics and Statistical Genetics Laboratories investigate the pattern of disease in families, particularly identical and non-identical twins, to assess the relative importance of genes and environment in a variety of important health problems.
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PMID
18357613
TITLE
Calculation of IBD probabilities with dense SNP or sequence data.
ABSTRACT
The probabilities that two individuals share 0, 1, or 2 alleles identical by descent (IBD) at a given genotyped marker locus are quantities of fundamental importance for disease gene and quantitative trait mapping and in family-based tests of association. Until recently, genotyped markers were sufficiently sparse that founder haplotypes could be modelled as having been drawn from a population in linkage equilibrium for the purpose of estimating IBD probabilities. However, with the advent of high-throughput single nucleotide polymorphism genotyping assays, this is no longer a reasonable assumption. Indeed, the imminent arrival of individual sequencing will enable high-density single nucleotide polymorphism genotyping on a scale for which current algorithms are not equipped. In this paper, we present a simple new model in which founder haplotypes are modelled as a Markov chain. Another important innovation is that genotyping errors are explicitly incorporated into the model. We compare results obtained using the new model to those obtained using the popular genetic linkage analysis package Merlin, with and without using the cluster model of linkage disequilibrium that is incorporated into that program. We find that the new model results in accuracy approaching that of Merlin with haplotype blocks, but achieves this with orders of magnitude faster run times. Moreover, the new algorithm scales linearly with number of markers, irrespective of density, whereas Merlin scales supralinearly. We also confirm a previous finding that ignoring linkage disequilibrium in founder haplotypes can cause errors in the calculation of IBD probabilities.
(c) 2008 Wiley-Liss, Inc.
DATE PUBLISHED
2008 Sep
HISTORY
PUBSTATUS PUBSTATUSDATE
pubmed 2008/03/22 09:00
medline 2008/10/24 09:00
entrez 2008/03/22 09:00
AUTHORS
NAME COLLECTIVENAME LASTNAME FORENAME INITIALS AFFILIATION AFFILIATIONINFO
Keith JM Keith Jonathan M JM School of Mathematical Sciences, Queensland University of Technology, Brisbane, Qld. 4001, Australia. j.keith.@qut.edu.au
McRae A McRae Allan A
Duffy D Duffy David D
Mengersen K Mengersen Kerrie K
Visscher PM Visscher Peter M PM
INVESTIGATORS
JOURNAL
VOLUME: 32
ISSUE: 6
TITLE: Genetic epidemiology
ISOABBREVIATION: Genet. Epidemiol.
YEAR: 2008
MONTH: Sep
DAY:
MEDLINEDATE:
SEASON:
CITEDMEDIUM: Internet
ISSN: 1098-2272
ISSNTYPE: Electronic
MEDLINE JOURNAL
MEDLINETA: Genet Epidemiol
COUNTRY: United States
ISSNLINKING: 0741-0395
NLMUNIQUEID: 8411723
PUBLICATION TYPE
PUBLICATIONTYPE TEXT
Journal Article
Research Support, Non-U.S. Gov't
Twin Study
COMMENTS AND CORRECTIONS
GRANTS
GENERAL NOTE
KEYWORDS
MESH HEADINGS
DESCRIPTORNAME QUALIFIERNAME
Algorithms
Alleles
Cluster Analysis
Computer Simulation
Genetic Markers
Haplotypes
Humans
Linkage Disequilibrium
Markov Chains
Models, Genetic
Models, Statistical
Polymorphism, Single Nucleotide
Quantitative Trait, Heritable
SUPPLEMENTARY MESH
GENE SYMBOLS
CHEMICALS
REGISTRYNUMBER NAMEOFSUBSTANCE
0 Genetic Markers
OTHER ID's