Skip Navigation


Bioinformatics Advance Access originally published online on March 5, 2008
Bioinformatics 2008 24(8):1106-1108; doi:10.1093/bioinformatics/btn087
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow All Versions of this Article:
24/8/1106    most recent
btn087v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Douglas, J. A.
Right arrow Articles by Sandefur, C. I.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Douglas, J. A.
Right arrow Articles by Sandefur, C. I.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 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

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.