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- Kurbasic, Azra, et al.
(författare)
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A general method for linkage disequilibrium correction for multipoint linkage and association.
- 2008
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Ingår i: Genetic Epidemiology. - : Wiley. - 0741-0395 .- 1098-2272. ; 32:7, s. 647-657
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Tidskriftsartikel (refereegranskat)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.
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- Kurbasic, Azra, et al.
(författare)
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Relative risks and effective number of meioses: A unified approach for general genetic models and phenotypes
- 2006
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Ingår i: Annals of Human Genetics. - : Wiley. - 1469-1809 .- 0003-4800. ; 70:6, s. 907-922
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Tidskriftsartikel (refereegranskat)abstract
- Many common diseases are known to have genetic components, but since they are non-Mendelian, i.e. a large number of genetic factors affect the phenotype, these components are difficult to localize. These traits are often called complex and analysis of siblings is a valuable tool for mapping them. It has been shown that the power of the affected relative pairs method to detect linkage of a disease susceptibility locus depends on the locus contribution to increased risk of relatives compared with population prevalence Risch, 1990a,b). In this paper we generalize calculation of relative risk to arbitrary phenotypes and genetic models, but also show that the relative risk can be split into the relative risk at the main locus and the relative risk due to interaction between the main locus and loci at other chromosomes. We demonstrate how the main locus contribution to the relative risk is related to probabilities of allele sharing identical by descent at the main locus, as well as power to detect linkage. To this end we use the effective number of meioses, introduced by Hossjer (2005a) as a convenient tool. Relative risks and effective number of meioses are computed for several genetic models with binary or quantitative phenotypes, with or without polygenic effects.
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- Kurbasic, Azra
(författare)
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Topics in Human Gene Mapping
- 2007
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis is interdisciplinary between Mathematical Statistics, Genetics, and Medicine. It mainly consists of topics in mathematical modelling of the correlation of inheritance of genes and disease in a family, a method called linkage analysis. It is organized as follows. First, a short introduction with the relevant background is given and then four papers are included. The first paper discusses hypothesis testing of linkage of a disease gene to a certain position on the chromosome. The focus is on the choice of lod scores and its relation to p-values. The second paper is a result of collaboration with the research groups in Lund and Denmark in the effort to localize the gene responsible for a malignant melanoma. Here, the theory presented in the first paper is used. The third paper concerns modelling of complex diseases, i.e. diseases governed by genetic contribution from at least two loci. We have studied the contribution of a particular locus to increased risk of relatives compared with population prevalence. Relative risk is modelled as the product of the relative risk at the main locus and the relative risk due to genetic contribution from other loci and shared environmental effects. Additionally, we show how this relative risk is related to probabilities of allele sharing identical by descent at the main locus and the power to detect linkage. The last paper contributes to the development of the algorithms used in the linkage and family based association analysis. One of the most demanding issues in these analyses is how to calculate the inheritance distribution at a certain position on the chromosome. The well established algorithms are based on the assumption that the markers used in the studies are in linkage equilibrium (LE). However, today's marker data have markers in linkage disequilibrium (LD). We develop a novel hidden Markov model algorithm for association and linkage analysis when markers are in LD.
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