A general method for linkage disequilibrium correction for multipoint linkage and association.
(2008) In Genetic Epidemiology 32(7). p.647-657- Abstract
- Lately, many different methods of linkage, association or joint analysis for family data have been invented and refined. Common to most of those is that they require a map of markers that are in linkage equilibrium. However, at the present day, high-density single nucleotide polymorphisms (SNPs) maps are both more inexpensive to create and they have lower genotyping error. When marker data is incomplete, the crucial and computationally most demanding moment in the analysis is to calculate the inheritance distribution at a certain position on the chromosome. Recently, different ways of adjusting traditional methods of linkage analysis to denser maps of SNPs in linkage disequilibrium (LD) have been proposed. We describe a hidden Markov model... (More)
- Lately, many different methods of linkage, association or joint analysis for family data have been invented and refined. Common to most of those is that they require a map of markers that are in linkage equilibrium. However, at the present day, high-density single nucleotide polymorphisms (SNPs) maps are both more inexpensive to create and they have lower genotyping error. When marker data is incomplete, the crucial and computationally most demanding moment in the analysis is to calculate the inheritance distribution at a certain position on the chromosome. Recently, different ways of adjusting traditional methods of linkage analysis to denser maps of SNPs in linkage disequilibrium (LD) have been proposed. We describe a hidden Markov model which generalizes the Lander-Green algorithm. It combines Markov chain for inheritance vectors with a Markov chain modelling founder haplotypes and in this way takes account for LD between SNPs. It can be applied to association, linkage or combined association and linkage analysis, general phenotypes and arbitrary score functions. We also define a joint likelihood for linkage and association that extends an idea of Kong and Cox (1997 Am. J. Hum. Genet. 61: 1179-1188) for pure linkage analysis. Genet. Epidemiol. 2008. (c) 2008 Wiley-Liss, Inc. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1154103
- author
- Kurbasic, Azra LU and Hössjer, Ola
- organization
- publishing date
- 2008
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- hidden Markov model • linkage • association • linkage disequilibrium • SNPs
- in
- Genetic Epidemiology
- volume
- 32
- issue
- 7
- pages
- 647 - 657
- publisher
- John Wiley & Sons Inc.
- external identifiers
-
- wos:000260871600007
- pmid:18481794
- scopus:58849166616
- ISSN
- 0741-0395
- DOI
- 10.1002/gepi.20339
- language
- English
- LU publication?
- yes
- id
- 5aaa1ad6-bd79-4102-bbad-636144a2096a (old id 1154103)
- date added to LUP
- 2016-04-01 12:20:16
- date last changed
- 2022-01-27 02:12:54
@article{5aaa1ad6-bd79-4102-bbad-636144a2096a,
abstract = {{Lately, many different methods of linkage, association or joint analysis for family data have been invented and refined. Common to most of those is that they require a map of markers that are in linkage equilibrium. However, at the present day, high-density single nucleotide polymorphisms (SNPs) maps are both more inexpensive to create and they have lower genotyping error. When marker data is incomplete, the crucial and computationally most demanding moment in the analysis is to calculate the inheritance distribution at a certain position on the chromosome. Recently, different ways of adjusting traditional methods of linkage analysis to denser maps of SNPs in linkage disequilibrium (LD) have been proposed. We describe a hidden Markov model which generalizes the Lander-Green algorithm. It combines Markov chain for inheritance vectors with a Markov chain modelling founder haplotypes and in this way takes account for LD between SNPs. It can be applied to association, linkage or combined association and linkage analysis, general phenotypes and arbitrary score functions. We also define a joint likelihood for linkage and association that extends an idea of Kong and Cox (1997 Am. J. Hum. Genet. 61: 1179-1188) for pure linkage analysis. Genet. Epidemiol. 2008. (c) 2008 Wiley-Liss, Inc.}},
author = {{Kurbasic, Azra and Hössjer, Ola}},
issn = {{0741-0395}},
keywords = {{hidden Markov model • linkage • association • linkage disequilibrium • SNPs}},
language = {{eng}},
number = {{7}},
pages = {{647--657}},
publisher = {{John Wiley & Sons Inc.}},
series = {{Genetic Epidemiology}},
title = {{A general method for linkage disequilibrium correction for multipoint linkage and association.}},
url = {{http://dx.doi.org/10.1002/gepi.20339}},
doi = {{10.1002/gepi.20339}},
volume = {{32}},
year = {{2008}},
}