TESS 2.3.1 – Bayesian Clustering using Tessellations and Markov models for Spatial Population Genetics

TESS 2.3.1

:: DESCRIPTION

TESS implements a Bayesian clustering algorithm for spatial population genetic analyses. It can perform both individual geographical assignment and admixture analysis. It is designed for seeking genetic discontinuities in continuous populations and estimating spatially varying individual admixture proportions.

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::DEVELOPER

the Computational and Mathematical Biology group in Grenoble

:: SCREENSHOTS

TESS

:: REQUIREMENTS

  • MacOsX / Windows

:: DOWNLOAD

 TESS 

:: MORE INFORMATION

Citation

C. Chen, E. Durand, F. Forbes, O. François (2007)
Bayesian clustering algorithms ascertaining spatial population structure: A new computer program and a comparison study,
Molecular Ecology Notes 7:747-756.