How to Install and Uninstall r-bioc-edger Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 18,2024

1. Install "r-bioc-edger" package

This guide covers the steps necessary to install r-bioc-edger on Ubuntu 21.10 (Impish Indri)

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

2. Uninstall "r-bioc-edger" package

In this section, we are going to explain the necessary steps to uninstall r-bioc-edger on Ubuntu 21.10 (Impish Indri):

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

3. Information about the r-bioc-edger package on Ubuntu 21.10 (Impish Indri)

Package: r-bioc-edger
Architecture: amd64
Version: 3.32.1+dfsg-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: 1350
Depends: r-base-core (>= 4.0.3-1), r-api-4.0, r-api-bioc-3.12, r-bioc-limma (>= 3.41.5), r-cran-locfit, r-cran-rcpp, libblas3 | libblas.so.3, libc6 (>= 2.29), libgcc-s1 (>= 3.0), liblapack3 | liblapack.so.3, libstdc++6 (>= 5.2)
Recommends: r-cran-statmod
Suggests: r-cran-jsonlite, r-cran-readr, r-bioc-rhdf5, r-bioc-biobase, r-bioc-annotationdbi, r-bioc-summarizedexperiment, r-bioc-org.hs.eg.db
Filename: pool/universe/r/r-bioc-edger/r-bioc-edger_3.32.1+dfsg-1_amd64.deb
Size: 1074916
MD5sum: 6b6e1837069b492bb04f1a752d26f614
SHA1: 1e98ba679b1173db6bfc722ece15ec1fcd711b2b
SHA256: fcf841e4def71ea401e158d50eeb6898d861bd87d7bfd8b0d0fa3483569ceb7e
SHA512: f7adc99ee466421621795819d06c94e56a3d3c2cf332023fecc140fdc7b9234f3d6b43851784ef75b7bb6bf9df0380f640e754430775cf60216aa8c6304083f8
Homepage: https://bioconductor.org/packages/edgeR/
Description-en: Empirical analysis of digital gene expression data in R
Bioconductor package for differential expression analysis of whole
transcriptome sequencing (RNA-seq) and digital gene expression
profiles with biological replication. It uses empirical Bayes
estimation and exact tests based on the negative binomial
distribution. It is also useful for differential signal analysis with
other types of genome-scale count data.
Description-md5: e9c6c6a168e9ee8c27a8db76210c4bdb