AutoClassWeb: a simple web interface for Bayesian clustering - Archive ouverte HAL
Autre Publication Scientifique Année : 2022

AutoClassWeb: a simple web interface for Bayesian clustering

Pierre Poulain
Jean-Michel Camadro

Résumé

Data clustering is a common exploration step in the omics era, in particular in genomics and proteomics. Bayesian clustering is a powerful algorithm that can classify several thousands of genes or proteins. AutoClass C, its original implementation handles missing data and determines automatically the best number of clusters but is unfortunately not user-friendly. We propose AutoClassWeb an easy-to-use web interface for Bayesian clustering with AutoClass. The project is implemented in Python and is published under the 3-Clauses BSD license. This web application is packaged as a Docker image and available in the BioContainer registry for better reproducibility. The code is available at https://github.com/pierrepo/autoclassweb along with a detailed documentation.
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Dates et versions

hal-03580909 , version 1 (18-02-2022)
hal-03580909 , version 2 (12-04-2022)

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Pierre Poulain, Jean-Michel Camadro. AutoClassWeb: a simple web interface for Bayesian clustering. 2022. ⟨hal-03580909v1⟩
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