How to Install and Uninstall garli Package on Ubuntu 21.04 (Hirsute Hippo)

Last updated: November 23,2024

1. Install "garli" package

Please follow the step by step instructions below to install garli on Ubuntu 21.04 (Hirsute Hippo)


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

Please follow the guidance below to uninstall garli on Ubuntu 21.04 (Hirsute Hippo):


    
        
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                sudo apt remove
            
                        
                garli
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the garli package on Ubuntu 21.04 (Hirsute Hippo)

Package: garli
Architecture: amd64
Version: 2.1-4
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: 1896
Depends: libc6 (>= 2.29), libgcc-s1 (>= 3.0), libncl2 (>= 2.1.18), libstdc++6 (>= 9)
Filename: pool/universe/g/garli/garli_2.1-4_amd64.deb
Size: 621072
MD5sum: e13a3becc714466e6601fed75db56f3f
SHA1: 4de6092806345c44dd6b5c8a207df134f60dd25c
SHA256: b23708063a5fd9ad0f40c06fe0d4339a3d36d2830afef7896374c5ce2ca3c5ad
SHA512: 4381f46bf5f3a1b8c542feb38251fdfdc6e36c66002948fda01b69b898590350ee488c66d6fe32bee132155f6bd0e73f2ea2dd918f4e98b796f74503424c67f7
Homepage: https://github.com/Ashod/garli
Description-en: phylogenetic analysis of molecular sequence data using maximum-likelihood
GARLI, Genetic Algorithm for Rapid Likelihood Inference is a program for
inferring phylogenetic trees. Using an approach similar to a classical
genetic algorithm, it rapidly searches the space of evolutionary trees
and model parameters to find the solution maximizing the likelihood
score. It implements nucleotide, amino acid and codon-based models of
sequence evolution, and runs on all platforms. The latest version adds
support for partitioned models and morphology-like datatypes.
Description-md5: 26bd1f70ecc029da7a39ce42be819b22