How to Install and Uninstall jmodeltest Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: January 23,2025

1. Install "jmodeltest" package

Please follow the step by step instructions below to install jmodeltest on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                jmodeltest
            
                    
    
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2. Uninstall "jmodeltest" package

This guide let you learn how to uninstall jmodeltest on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                jmodeltest
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the jmodeltest package on Ubuntu 20.10 (Groovy Gorilla)

Package: jmodeltest
Architecture: all
Version: 2.1.10+dfsg-9
Priority: optional
Section: universe/science
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Med Packaging Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 2677
Depends: alter-sequence-alignment, libmpj-java, libpal-java, java-wrappers, phyml
Filename: pool/universe/j/jmodeltest/jmodeltest_2.1.10+dfsg-9_all.deb
Size: 976244
MD5sum: a2a8839e91393846ff1760e759fa39c3
SHA1: 9e62752475da71ae2a3962b057cbda51b093bbaa
SHA256: 536bc808bb285d45b5301cfa5732bfea3833f00854b54dce9504a7e49b8c3071
SHA512: 26d04f2fd7132ed370712dc05e1ee77d7f67608e32c7a353246b17ffe96de7a95ec62cfcf7af35f5435d5f8523a3e8e43990b37f35bb51613ce92e761490d840
Homepage: https://github.com//ddarriba/jmodeltest2
Description-en: HPC selection of models of nucleotide substitution
jModelTest is a tool to carry out statistical selection of best-fit
models of nucleotide substitution. It implements five different model
selection strategies: hierarchical and dynamical likelihood ratio tests
(hLRT and dLRT), Akaike and Bayesian information criteria (AIC and BIC),
and a decision theory method (DT). It also provides estimates of model
selection uncertainty, parameter importances and model-averaged
parameter estimates, including model-averaged tree topologies.
jModelTest 2 includes High Performance Computing (HPC) capabilities and
additional features like new strategies for tree optimization, model-
averaged phylogenetic trees (both topology and branch length), heuristic
filtering and automatic logging of user activity.
Description-md5: f27877e220ca8710502bc000284112cb