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Biostatistics Advance Access published online on December 14, 2005
Biostatistics, doi:10.1093/biostatistics/kxj012
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© The Author 2005. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.
Received April 19, 2005
Revised November 21, 2005
Accepted December 7, 2005

Article

Incorporating interference into linkage analysis for experimental crosses

Nicola J. Armstrong 1 *, Mary Sara McPeek 2, and Terence P. Speed 3

1 Department of Mathematics, Vrije Universiteit, 1081HV Amsterdam, The Netherlands
2 Department of Statistics, University of Chicago, Chicago, Illinois 60637
3 Department of Statistics, University of California at Berkeley, CA 94720; Division of Genetics and Bioinformatics, Walter and Eliza Hall Institute of Medical Re-search, Melbourne, Australia

* To whom correspondence should be addressed.
Nicola J. Armstrong, E-mail: nicola{at}few.vu.nl


  Abstract

The phenomenon of interference in genetic recombination is well known and studied in a wide variety of organisms. Multilocus linkage analysis, which makes use of recombination patterns among all genetic markers simultaneously, is routinely used with data on humans and experimental organisms to build genetic maps. It is also used to try to determine the gene(s) involved in traits of interest, such as common diseases. Most linkage analyses performed today ignore the occurrence of genetical interference. We present an extension to the Lander-Green algorithm for experimental crosses (backcross and intercross) to incorporate crossover interference according to the {chi}2 model. Simulation results show the impact of using this model on the accuracy of estimated genetic maps.

Keywords: Crossover interference; linkage analysis; hidden Markov model.
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