Hidden Markov Modelling Techniques for Haplotype Analysis

Abstract. A hidden Markov model is introduced for descriptive modelling the mosaic–like structures of haplotypes, due to iterated recombinations within a population. Methods using the minimum description length principle are given for fitting such models to training data. Possible applications of the models are delineated, and some preliminary analysis results on real sets of haplotypes are reported, demonstrating the potential of our methods.

• Type: Conference
• Year: 2004
• Where: ALT
• Authors: Mikko Koivisto, Teemu Kivioja, Heikki Mannila, Pasi Rastas, Esko Ukkonen
• Keywords: ALT 2004, Hidden Markov Model, Machine Learning, Minimum Description Length, Real Sets