PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Approximate inference methods for genetic linkage analysis
Kees Albers
(2008) PhD thesis, Radboud University Nijmegen.

Abstract

1. Introduction 2. The Cluster Variation Method for efficient linkage analysis in extended pedigrees 3. Haplotype inference in general pedigrees using the Cluster Variation Method 4. Haplotype reconstruction in pedigrees from genotypes with errors 5. Multipoint approximations of identity by descent probabilities for accurate linkage analysis of distantly related individuals 6. Modeling linkage disequilibrium in exact linkage computations: a comparison of first order Markov approaches and the clustered markers appoach

EPrint Type:Thesis (PhD)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:4863
Deposited By:Bert Kappen
Deposited On:24 March 2009