How to Install and Uninstall macs Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 02,2024

1. Install "macs" package

This guide let you learn how to install macs on Ubuntu 21.10 (Impish Indri)


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

This tutorial shows how to uninstall macs on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                macs
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the macs package on Ubuntu 21.10 (Impish Indri)

Package: macs
Architecture: amd64
Version: 2.2.7.1-3build2
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: 5646
Depends: python3 (<< 3.10), python3 (>= 3.9~), python3-numpy, python3:any, libc6 (>= 2.29)
Filename: pool/universe/m/macs/macs_2.2.7.1-3build2_amd64.deb
Size: 2496472
MD5sum: 1e9ab43b57f92480093ea3d7b25532ac
SHA1: cb69358ce5a8a86aba2e580acb419aabe234aa91
SHA256: 496199edd60f72c1f7fd22b3b3a9fe93fb33e227cc6c459880a42931d388a486
SHA512: d80ed2b2c56b35f798cce57811bb68a1f1f79cdcc79bba6c20bfb600e6189bafa7af98310a0f421ca27706919befa50f9a404305ceffd4147acc4b54dec4695e
Homepage: https://github.com/taoliu/MACS/
Description-en: Model-based Analysis of ChIP-Seq on short reads sequencers
MACS empirically models the length of the sequenced ChIP fragments, which
tends to be shorter than sonication or library construction size estimates,
and uses it to improve the spatial resolution of predicted binding sites.
MACS also uses a dynamic Poisson distribution to effectively capture local
biases in the genome sequence, allowing for more sensitive and robust
prediction. MACS compares favorably to existing ChIP-Seq peak-finding
algorithms, is publicly available open source, and can be used for ChIP-Seq
with or without control samples.
Description-md5: ea92f8fedfe04d3f07954aa006c99da9