Close
Help




JOURNAL

Evolutionary Bioinformatics

1,227,569 Journal Article Views | Journal Analytics

Arlequin (version 3.0): An integrated software package for population genetics data analysis

Submit a Paper



Publication Date: 23 Feb 2007

Journal: Evolutionary Bioinformatics

Citation: Evolutionary Bioinformatics Online 2005:1 47-50

Laurent Excoffier, Guillaume Laval, Stefan Schneider

Computational and Molecular Population Genetics Lab, , Zoological Institute, University of Berne, Baltzerstrasse 6, 3012 Berne, Switzerland

Abstract: Arlequin ver 3.0 is a software package integrating several basic and advanced methods for population genetics data analysis, like the computation of standard genetic diversity indices, the estimation of allele and haplotype frequencies, tests of departure from linkage equilibrium, departure from selective neutrality and demographic equilibrium, estimation or parameters from past population expansions, and thorough analyses of population subdivision under the AMOVA framework. Arlequin 3 introduces a completely new graphical interface written in C++, a more robust semantic analysis of input files, and two new methods: a Bayesian estimation of gametic phase from multi-locus genotypes, and an estimation of the parameters of an instantaneous spatial expansion from DNA sequence polymorphism. Arlequin can handle several data types like DNA sequences, microsatellite data, or standard multilocus genotypes. A Windows version of the software is freely available on http://cmpg.unibe.ch/software/arlequin3.



Downloads

PDF  (102.95 KB PDF FORMAT)

RIS citation   (ENDNOTE, REFERENCE MANAGER, PROCITE, REFWORKS)

BibTex citation   (BIBDESK, LATEX)

XML






What Your Colleagues Say About Evolutionary Bioinformatics
My co-authors and I had a very positive experience with the review and publication process in Evolutionary Bioinformatics.  The reviewers were rapid and on point, and publication was also rapid after we made the necessary revisions.
Professor Steven Salzberg (Director, Center for Computational Biology, Johns Hopkins University School of Medicine, Baltimore, MD, USA)
More Testimonials

Quick Links


Follow Us We make it easy to find new research papers.