How to Install and Uninstall r-bioc-dada2 Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: May 20,2024

1. Install "r-bioc-dada2" package

Please follow the instructions below to install r-bioc-dada2 on Ubuntu 20.10 (Groovy Gorilla)

$ sudo apt update $ sudo apt install r-bioc-dada2

2. Uninstall "r-bioc-dada2" package

Please follow the step by step instructions below to uninstall r-bioc-dada2 on Ubuntu 20.10 (Groovy Gorilla):

$ sudo apt remove r-bioc-dada2 $ sudo apt autoclean && sudo apt autoremove

3. Information about the r-bioc-dada2 package on Ubuntu 20.10 (Groovy Gorilla)

Package: r-bioc-dada2
Architecture: amd64
Version: 1.16.0+dfsg-1build1
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: 2193
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-api-bioc-3.11, r-cran-rcpp (>= 0.12.0), r-bioc-biostrings (>= 2.42.1), r-cran-ggplot2 (>= 2.1.0), r-cran-reshape2 (>= 1.4.1), r-bioc-shortread (>= 1.32.0), r-cran-rcppparallel (>= 4.3.0), r-bioc-iranges (>= 2.6.0), r-bioc-xvector (>= 0.16.0), r-bioc-biocgenerics (>= 0.22.0), libc6 (>= 2.29), libgcc-s1 (>= 3.0), libstdc++6 (>= 5.2), libtbb2 (>= 2017~U7)
Suggests: r-cran-knitr, r-cran-rmarkdown, libjs-jquery
Filename: pool/universe/r/r-bioc-dada2/r-bioc-dada2_1.16.0+dfsg-1build1_amd64.deb
Size: 1875904
MD5sum: 9467e4839cca5acaf812bf1f06ca079f
SHA1: 3b19525b8668fc3542ab60fb187cbd06c1575512
SHA256: d6dfde2e43f9638cec78af8eb839273ab7a31a609e494ba9194bc7250db60383
SHA512: 36a3caf78483e078cebadb3d12150ac9d8b36c33ff0e932b97ca76537c3155a33996eea56e1395336b83273a4d12a111603400223535f4662d7ab3e6f495fd7f
Homepage: https://bioconductor.org/packages/dada2/
Description-en: sample inference from amplicon sequencing data
The dada2 package contributes to software workflows to interpret
sequencing data from microbiota - the relative abundance of
bacterial and/or yeast, typically measured in the gut.
It infers exact amplicon sequence
variants (ASVs) from high-throughput amplicon sequencing data,
replacing the coarser and less accurate OTU clustering approach.
The dada2 pipeline takes as input demultiplexed fastq files, and
outputs the sequence variants and their sample-wise abundances
after removing substitution and chimera errors. Taxonomic
classification is available via a native implementation of the RDP
naive Bayesian classifier, and species-level assignment to 16S
rRNA gene fragments by exact matching.
Description-md5: 3fa0d6dceb2f30972ee5a7c11349bf26