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RNAseq123

RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR


Bioconductor version: Release (3.18)

R package that supports the F1000Research workflow article on RNA-seq analysis using limma, Glimma and edgeR by Law et al. (2016).

Author: Charity Law, Monther Alhamdoosh, Shian Su, Xueyi Dong, Luyi Tian, Gordon Smyth and Matthew Ritchie

Maintainer: Matthew Ritchie <mritchie at wehi.edu.au>

Citation (from within R, enter citation("RNAseq123")):

Installation

To install this package, start R (version "4.3") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("RNAseq123")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("RNAseq123")
A guide to creating design matrices for gene expression experiments (English version) HTML R Script
RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR (Chinese version) HTML R Script
RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR (English version) HTML R Script

Details

biocViews GeneExpressionWorkflow, ImmunoOncologyWorkflow, Workflow
Version 1.26.0
License Artistic-2.0
Depends R (>= 3.3.0), Glimma(>= 1.1.9), limma, edgeR, gplots, RColorBrewer, Mus.musculus, R.utils, TeachingDemos, statmod, BiocWorkflowTools
Imports
System Requirements
URL https://f1000research.com/articles/5-1408/v3
See More
Suggests knitr, rmarkdown, BiocStyle
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package RNAseq123_1.26.0.tar.gz
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/RNAseq123
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/RNAseq123
Package Short Url https://bioconductor.org/packages/RNAseq123/
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