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.

::DEVELOPER

the Computational and Mathematical Biology group in Grenoble

:: SCREENSHOTS

:: 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.

SpaCEM3 2.0 – Spatial Clustering with EM and Markov Model

SpaCEM³ 2.0

:: DESCRIPTION

The SpaCEM³ software is dedicated to Spatial Clustering with EM and Markov Models. It proposes a variety of algorithms for supervised and unsupervised classification of multidimensional and spatially-located data. The main techniques use the EM algorithm for soft clustering and Markov Random Fields (MRF) for spatial modelling. The learning and inference parts are based on recent developments in mean field-like approximations. Its applications range from image segmentation (e.g. tissue detection in MRI, retrieval of planet surface properties from hyperspectral satellite images…) to gene clustering (e.g. biological module detection), remote sensing and mapping epidemics of ecological species.

::DEVELOPER

SpaCEM³ Team

:: SCREENSHOTS

:: REQUIREMENTS

Windows/Linux

:: DOWNLOAD

SpaCEM³

:: MORE INFORMATION

Citation

Bioinformatics. 2011 Mar 15;27(6):881-2. doi: 10.1093/bioinformatics/btr034. Epub 2011 Feb 3.
SpaCEM3: a software for biological module detection when data is incomplete, high dimensional and dependent.
Vignes M, Blanchet J, Leroux D, Forbes F.

Scimm 0.3.0 – Sequence Clustering with Interpolated Markov Models

Scimm 0.3.0

:: DESCRIPTION

Scimm is a tool for unsupervised clustering of metagenomic sequences using interpolated Markov models.

::DEVELOPER

David Kelley ,Steven Salzberg

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
Python

:: DOWNLOAD

Scimm

:: MORE INFORMATION

Citation:

Kelley DR, Salzberg SL.
Clustering metagenomic sequences with interpolated Markov models.
BMC Bioinformatics 11:544 2010.