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

Last updated: May 19,2024

1. Install "grinder" package

This guide let you learn how to install grinder on Ubuntu 20.10 (Groovy Gorilla)


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

Here is a brief guide to show you how to uninstall grinder on Ubuntu 20.10 (Groovy Gorilla):


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

Package: grinder
Architecture: all
Version: 0.5.4-5
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: 245
Depends: perl, libbio-perl-perl, libgetopt-euclid-perl, libmath-random-mt-perl
Filename: pool/universe/g/grinder/grinder_0.5.4-5_all.deb
Size: 79688
MD5sum: 5657021f79ba825d69c618a26ec4fbc7
SHA1: 97200f16b73b1fdc2751fc240c419cbf6bfd5a3d
SHA256: 5598ce0ddd857a244952cca4dba3b2dd6035789774c24dbfe95239260c807216
SHA512: 69a9fb3fbab6bf8230c309d547728b69f03b862eb0b37c5b567145e62aefb9497a34ac50058c0f56c0b381a944d7b9bd00145062d06c1835f7df614649699443
Homepage: https://sourceforge.net/projects/biogrinder/
Description-en: Versatile omics shotgun and amplicon sequencing read simulator
Grinder is a versatile program to create random shotgun and amplicon sequence
libraries based on DNA, RNA or proteic reference sequences provided in a
FASTA file.
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Grinder can produce genomic, metagenomic, transcriptomic, metatranscriptomic,
proteomic, metaproteomic shotgun and amplicon datasets from current
sequencing technologies such as Sanger, 454, Illumina. These simulated
datasets can be used to test the accuracy of bioinformatic tools under
specific hypothesis, e.g. with or without sequencing errors, or with low or
high community diversity. Grinder may also be used to help decide between
alternative sequencing methods for a sequence-based project, e.g. should the
library be paired-end or not, how many reads should be sequenced.
Description-md5: 83e4b80a1bd0288759d7cb1739440cc0