How to Install and Uninstall alien-hunter Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: May 10,2024

1. Install "alien-hunter" package

This guide let you learn how to install alien-hunter on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                alien-hunter
            
                    
    
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2. Uninstall "alien-hunter" package

This guide covers the steps necessary to uninstall alien-hunter on Ubuntu 20.10 (Groovy Gorilla):


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

Package: alien-hunter
Architecture: all
Version: 1.7-7
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: 91
Depends: libbytecode-java, libbiojava-java, libcommons-cli-java, libcommons-collections3-java, libcommons-dbcp-java, libcommons-pool-java
Suggests: bioperl
Filename: pool/universe/a/alien-hunter/alien-hunter_1.7-7_all.deb
Size: 28820
MD5sum: 728286b003781a990c867c7067ee1d54
SHA1: dcf5c8d9229c5b3af445e3bd7dea617a17ea2777
SHA256: b191078653632309179df2b5e26dc467f2bb32920e55589af3ba4181b4470c34
SHA512: 7f6d8f369ea14ea68fc29b43d84841dd5a944673c936387e20e9bd182995885abe94524f811f495a1696719c23bb5b8ed11b76c9764eb75a2a093c506c228930
Homepage: http://www.sanger.ac.uk/science/tools/alien-hunter
Description-en: Interpolated Variable Order Motifs to identify horizontally acquired DNA
Alien_hunter is an application for the prediction of putative
Horizontal Gene Transfer (HGT) events with the implementation of
Interpolated Variable Order Motifs (IVOMs). An IVOM approach
exploits compositional biases using variable order motif distributions
and captures more reliably the local composition of a sequence compared
to fixed-order methods. Optionally the predictions can be parsed into a
2-state 2nd order Hidden Markov Model (HMM), in a change-point detection
framework, to optimize the localization of the boundaries of the
predicted regions. The predictions (embl format) can be automatically
loaded into Artemis genome viewer freely available at:
http://www.sanger.ac.uk/Software/Artemis/.
Description-md5: 5f7c91ddef3ac915fd4f61d66745892f