Skip Navigation



Bioinformatics Advance Access published online on July 14, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti584
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow All Versions of this Article:
21/18/3686    most recent
bti584v1
Right arrow Alert me when this article is cited
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 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 Peng, B.
Right arrow Articles by Kimmel, M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Peng, B.
Right arrow Articles by Kimmel, M.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org
Received May 13, 2005
Revised July 8, 2005
Accepted July 13, 2005

Applications note

simuPOP: a forward-time population genetics simulation environment

Bo Peng 1* and Marek Kimmel 1

1 Department of Statistics, Rice University 6100 Main St. MS138 Houston, TX, 77005

* To whom correspondence should be addressed.
Bo Peng, E-mail: bpeng{at}rice.edu


  Abstract

Summary: simuPOP is a forward-time population genetics simulation environment. The core of simuPOP is a scripting language (Python) that provides a large number of objects and functions to manipulate populations, and a mechanism to evolve populations forward in time. Using this R/Splus-like environment, users can create, manipulate and evolve populations interactively, or write a script and run it as a batch file. Due to its flexible and extensible design, simuPOP can simulate large and complex evolutionary processes with ease. At a more user-friendly level, simuPOP provides an increasing number of built-in scripts that perform simulations ranging from basic population genetics models to generating datasets under complex evolutionary scenarios.

Availability: simuPOP is freely available at http://www.stat.rice.edu/~bpeng/simuPOP.htm, distributed under GPL license.


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


This article has been cited by other articles:


Home page
 BioinformaticsHome page
S. Neuenschwander, F. Hospital, F. Guillaume, and J. Goudet
quantiNemo: an individual-based program to simulate quantitative traits with explicit genetic architecture in a dynamic metapopulation
Bioinformatics, July 1, 2008; 24(13): 1552 - 1553.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
B. Peng and C. I. Amos
Forward-time simulations of non-random mating populations using simuPOP
Bioinformatics, June 1, 2008; 24(11): 1408 - 1409.
[Abstract] [Full Text] [PDF]

Home page
 GeneticsHome page
B. Padhukasahasram, P. Marjoram, J. D. Wall, C. D. Bustamante, and M. Nordborg
Exploring Population Genetic Models With Recombination Using Efficient Forward-Time Simulations
Genetics, April 1, 2008; 178(4): 2417 - 2427.
[Abstract] [Full Text] [PDF]

Home page
 GeneticsHome page
C. J. Hoggart, M. Chadeau-Hyam, T. G. Clark, R. Lampariello, J. C. Whittaker, M. De Iorio, and D. J. Balding
Sequence-Level Population Simulations Over Large Genomic Regions
Genetics, November 1, 2007; 177(3): 1725 - 1731.
[Abstract] [Full Text] [PDF]

Home page
 GeneticsHome page
B. Peng and M. Kimmel
Simulations Provide Support for the Common Disease-Common Variant Hypothesis
Genetics, February 1, 2007; 175(2): 763 - 776.
[Abstract] [Full Text] [PDF]

Home page
 jvmeHome page
M. T. Ryan and T. Sweeney
Integrating Molecular Biology into the Veterinary Curriculum
J Vet Med Educ, January 1, 2007; 34(5): 658 - 673.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
F. Guillaume and J. Rougemont
Nemo: an evolutionary and population genetics programming framework
Bioinformatics, October 15, 2006; 22(20): 2556 - 2557.
[Abstract] [Full Text] [PDF]


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.