How to Install and Uninstall alien-hunter Package on Ubuntu 21.04 (Hirsute Hippo)

Last updated: November 06,2024

1. Install "alien-hunter" package

Please follow the guidelines below to install alien-hunter on Ubuntu 21.04 (Hirsute Hippo)


    
        
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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

Please follow the step by step instructions below to uninstall alien-hunter on Ubuntu 21.04 (Hirsute Hippo):


    
        
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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 21.04 (Hirsute Hippo)

Package: alien-hunter
Architecture: all
Version: 1.7-8
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: 112
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_1.7-8_all.deb
Size: 28320
MD5sum: 50ef9f5726cf0aa770a9ba86c120a9af
SHA1: eaf8c5667615b2643cb4aec5e9484ca2d64de1fc
SHA256: 7db8d6624c5221d4c857de5ba024516bd1820caae54e029039841fe863576fa8
SHA512: 742df9267ad825054f2cbf99f0daff4f91ea042e2c1897fe317a55a4b15db55d2f09e5716431e3edf4a6b3eb82f154d0f6ef71464d1b34e87be0fc7c72254471
Homepage: https://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