A flexible forward simulator for populations subject to selection and demography

• Published in: Bioinformatics Vol. 24; no. 23; pp. 2786 - 2787
• Main Author: Hernandez, Ryan D.
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 01.12.2008; Oxford Publishing Limited (England)
• Subjects: Algorithms; Applications Note; Biological and medical sciences; Biological Evolution; Computer Simulation; Demography; Fundamental and applied biological sciences. Psychology; General aspects; Genetic diversity; Genetics, Population; Genome, Human; Humans; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Models, Genetic; Population - genetics; Selection, Genetic; Software; Population; Bioinformatics; Selection
• ISSN: 1367-4803; 1367-4811; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/btn522

This article introduces a new forward population genetic simulation program that can efficiently generate samples from populations with complex demographic histories under various models of natural selection. The program (SFS_CODE) is highly flexible, allowing the user to simulate realistic genomic regions with several loci evolving according to a variety of mutation models (from simple to context-dependent), and allows for insertions and deletions. Each locus can be annotated as either coding or non-coding, sex-linked or autosomal, selected or neutral, and have an arbitrary linkage structure (from completely linked to independent). Availability: The source code (written in the C programming language) is available at http://sfscode.sourceforge.net, and a web server (http://cbsuapps.tc.cornell.edu/sfscode.aspx) allows the user to perform simulations using the high-performance computing cluster hosted by the Cornell University Computational Biology Service Unit. Contact: rhernandez@uchicago.edu Supplementary information: An extensive user's manual, perfor-mance statistics, and comparisons of patterns of genetic variation generated by SFS_CODE to theoretical expectations under various non-stationary demographic histories and models of natural selection are available on the project website: http://sfscode.sourceforge.net.