How to Install and Uninstall r-bioc-gosemsim Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: May 02,2024

1. Install "r-bioc-gosemsim" package

Please follow the guidance below to install r-bioc-gosemsim on Ubuntu 20.10 (Groovy Gorilla)

$ sudo apt update $ sudo apt install r-bioc-gosemsim

2. Uninstall "r-bioc-gosemsim" package

This tutorial shows how to uninstall r-bioc-gosemsim on Ubuntu 20.10 (Groovy Gorilla):

$ sudo apt remove r-bioc-gosemsim $ sudo apt autoclean && sudo apt autoremove

3. Information about the r-bioc-gosemsim package on Ubuntu 20.10 (Groovy Gorilla)

Package: r-bioc-gosemsim
Architecture: amd64
Version: 2.14.1-1
Priority: optional
Section: universe/gnu-r
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian R Packages Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 1038
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-api-bioc-3.11, r-bioc-annotationdbi, r-bioc-go.db, r-cran-rcpp, libc6 (>= 2.29), libgcc-s1 (>= 3.0), libstdc++6 (>= 5.2)
Recommends: r-cran-testthat
Suggests: r-bioc-annotationhub, r-cran-biocmanager, r-cran-knitr, r-bioc-org.hs.eg.db
Filename: pool/universe/r/r-bioc-gosemsim/r-bioc-gosemsim_2.14.1-1_amd64.deb
Size: 829204
MD5sum: 15ebaffd53920ff7729973e540f9bfaa
SHA1: 03b65ff5e787b7514421163aaf2c0031985ead3f
SHA256: b1d1f9c9f04481be35ee194dab1b20f98b7cc553b0177b95e43605fe1c1a0957
SHA512: f3d70463b775690bbbbf4ca24c52fefa12e4e1c96f8a8c4e8c9a6e4393a875794d5e0993697d5bfee01ad2bd0689ecf7630cbc0838c0b20a2572c9c8ca492944
Homepage: https://bioconductor.org/packages/GOSemSim/
Description-en: GO-terms semantic similarity measures
The semantic comparisons of Gene Ontology (GO) annotations provide
quantitative ways to compute similarities between genes and gene groups,
and have became important basis for many bioinformatics analysis approaches.
GOSemSim is an R package for semantic similarity computation among GO terms,
sets of GO terms, gene products and gene clusters. GOSemSim implemented five
methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively.
Description-md5: 445dc86df6bb0bc1cf75d0e4d75553a6