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Markov processes for modeling and analyzing a new genetic mapping method

Part of: Markov processes

Published online by Cambridge University Press:  14 July 2016

Eleanor Feingold
Eleanor Feingold*
Affiliation:
Stanford University
*
∗ Present address: Division of Biostatistics, Emory University School of Public Health, 1599 Clifton Road NE, Atlanta, GA 30329, USA.
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Abstract

This paper describes a set of stochastic processes that is useful for modeling and analyzing a new genetic mapping method. Some of the processes are Markov chains, and some are best described as functions of Markov chains. The central issue is boundary-crossing probabilities, which correspond to p-values for the existence of genes for particular traits. The methods elaborated by Aldous (1989) provide very accurate approximate p-values, as spot-checked against simulations.

Keywords

MARKOV CHAINBOUNDARY-CROSSING PROBABILITYPOISSON APPROXIMATION

MSC classification

Primary: 60J27: Continuous-time Markov processes on discrete state spaces
Secondary: 92D10: Genetics
Type
Research Papers
Information
Journal of Applied Probability , Volume 30 , Issue 4 , December 1993 , pp. 766 - 779
Copyright
Copyright © Applied Probability Trust 1993 

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References

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