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

Last updated: May 20,2024

1. Install "kmc" package

Here is a brief guide to show you how to install kmc on Ubuntu 21.04 (Hirsute Hippo)


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

Here is a brief guide to show you how to uninstall kmc on Ubuntu 21.04 (Hirsute Hippo):


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

Package: kmc
Architecture: amd64
Version: 3.1.1+dfsg-3
Built-Using: simde (= 0.7.0-2)
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: 3985
Depends: libbz2-1.0, libc6 (>= 2.14), libgcc-s1 (>= 3.0), libstdc++6 (>= 6), zlib1g (>= 1:1.2.6)
Filename: pool/universe/k/kmc/kmc_3.1.1+dfsg-3_amd64.deb
Size: 883404
MD5sum: 8709bbd850773d538da4cee5459eadf1
SHA1: ba483a5a430a5fd37ca11b4e0855ab3b507522a2
SHA256: c4981a27f98489c6969c3a27adca778ca7696ebeda0a7beafa9a1872d45d304e
SHA512: 9759e19079a8a3ae74bf4157904119f0c59e20440cbd4dc34884a8e0c88aaf528e0927cdb95ca62a1cd7deaee4f1aabc5b639677f629def45ed6bf5140fcf14c
Homepage: http://sun.aei.polsl.pl/kmc
Description-en: count kmers in genomic sequences
The kmc software is designed for counting k-mers (sequences of
consecutive k symbols) in a set of reads. K-mer counting is
important for many bioinformatics applications, e.g. developing de Bruijn
graph assemblers.
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Building de Bruijn graphs is a commonly used approach for genome
assembly with data from second-generation sequencing.
Unfortunately, sequencing errors (frequent in practice)
result in huge memory requirements for de Bruijn graphs, as well
as long build time. One of the popular approaches to handle this
problem is filtering the input reads in such a way that unique k-mers
(very likely obtained as a result of an error) are discarded.
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Thus, KMC scans the raw reads and produces a compact representation
of all non-unique reads accompanied with number of their occurrences.
The algorithm implemented in KMC makes use mostly of disk space rather
than RAM, which allows one to use KMC even on rather typical personal
computers. When run on high-end servers (what is necessary for KMC
competitors) it outperforms them in both memory requirements and
speed of computation. The disk space necessary for computation is in
order of the size of input data (usually it is smaller).
Description-md5: ebf89f936ea92086de01b356a765be39