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A Monte Carlo approach to calculating probabilities for continuous identity by descent data

Part of: Probabilistic methods, simulation and stochastic differential equations Special processes

Published online by Cambridge University Press:  14 July 2016

Sharon Browning
Sharon Browning*
Affiliation:
North Carolina State University
*
∗Postal address: Department of Statistics, North Carolina State University, Raleigh, NC 27695-8203, USA. Email address: browning@stat.nscu.edu
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Abstract

Two related individuals are identical by descent at a genetic locus if they share the same gene copy at that locus due to inheritance from a recent common ancestor. We consider idealized continuous identity by descent (IBD) data in which IBD status is known continuously along chromosomes. IBD data contains information about the relationship between the two individuals, and about the underlying crossover processes. We present a Monte Carlo method for calculating probabilities for IBD data. The method is not restricted to Haldane's Poisson process model of crossing-over but may be used with other models including the chi-square, Kosambi renewal and Sturt models. Results of a simulation study demonstrate that IBD data can be used to distinguish between alternative models for the crossover process.

Keywords

GeneticsMonte Carloidentity by descentchiasma interference

MSC classification

Primary: 92D10: Genetics 65C05: Monte Carlo methods
Secondary: 60K40: Other physical applications of random processes
Type
Research Papers
Information
Journal of Applied Probability , Volume 37 , Issue 3 , September 2000 , pp. 850 - 864
Copyright
Copyright © Applied Probability Trust 2000 

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