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

Last updated: May 22,2024

1. Install "r-bioc-scater" package

This is a short guide on how to install r-bioc-scater on Ubuntu 21.10 (Impish Indri)

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

2. Uninstall "r-bioc-scater" package

This is a short guide on how to uninstall r-bioc-scater on Ubuntu 21.10 (Impish Indri):

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

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

Package: r-bioc-scater
Architecture: all
Version: 1.18.3+ds-4
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: 661
Depends: r-base-core (>= 4.0.4-1build1), r-api-4.0, r-api-bioc-3.12, r-bioc-singlecellexperiment, r-cran-ggplot2, r-cran-gridextra, r-cran-matrix, r-bioc-biocgenerics, r-bioc-s4vectors, r-bioc-summarizedexperiment, r-bioc-delayedarray, r-bioc-delayedmatrixstats, r-bioc-biocneighbors, r-bioc-biocsingular, r-bioc-biocparallel, r-bioc-scuttle, r-cran-rlang, r-cran-ggbeeswarm, r-cran-viridis
Recommends: r-cran-testthat, r-bioc-destiny, r-cran-uwot, r-cran-nmf, r-cran-rtsne, r-bioc-dropletutils, r-cran-pheatmap
Suggests: r-bioc-biocstyle, r-bioc-biomart, r-cran-cowplot, r-cran-knitr, r-bioc-scrnaseq, r-cran-robustbase, r-cran-rmarkdown, r-bioc-biobase
Filename: pool/universe/r/r-bioc-scater/r-bioc-scater_1.18.3+ds-4_all.deb
Size: 453700
MD5sum: 512ad6e69de38d3c530ff020ac7abc7f
SHA1: 9076101ea342bb836fd9bff702982184d833467d
SHA256: 35cf041b724c364a4e84397443cf593a10f26e59eaf9f1adfd83d1542aa77f8d
SHA512: dccef5cb80c58fdcd044fb85333620a647a1cfed274afd9521ae7f57b4921df8a7d5634b1aae0551a22c3f8fe7d7a1e21ddce67b07b150fb48b8ac54268da038
Homepage: https://bioconductor.org/packages/scater/
Description-en: Single-Cell Analysis Toolkit for Gene Expression Data in R
A collection of tools for doing various analyses of
single-cell RNA-seq gene expression data, with a focus on
quality control and visualization.
Description-md5: bf6ae79152eb75c733d537b74fa2f65c