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Bioinformatics Advance Access originally published online on March 5, 2008
Bioinformatics 2008 24(8):1106-1108; doi:10.1093/bioinformatics/btn087
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

PedMine—a simulated annealing algorithm to identify maximally unrelated individuals in population isolates

Julie A. Douglas 1,2,* and Conner I. Sandefur 2

1Department of Human Genetics and 2Program in Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA

*To whom correspondence should be addressed.


  Abstract

Summary: In family-based genetic studies, it is often useful to identify a subset of unrelated individuals. When such studies are conducted in population isolates, however, most if not all individuals are often detectably related to each other. To identify a set of maximally unrelated (or equivalently, minimally related) individuals, we have implemented simulated annealing, a general-purpose algorithm for solving difficult combinatorial optimization problems. We illustrate our method on data from a genetic study in the Old Order Amish of Lancaster County, Pennsylvania, a population isolate derived from a modest number of founders. Given one or more pedigrees, our program automatically and rapidly extracts a fixed number of maximally unrelated individuals.

Availability: http://www.hg.med.umich.edu/labs/douglaslab/software.html (version 1.0.0)

Contact: jddoug{at}umich.edu

Associate Editor: Martin Bishop

Received on February 5, 2008; revised on February 28, 2008; accepted on March 3, 2008

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