Bioconductor version: Release (3.13)
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")
):
To install this package, start R (version "4.1") and enter:
if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("RNAseq123")
For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("RNAseq123")
HTML | R Script | 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) |
biocViews | GeneExpressionWorkflow, ImmunoOncologyWorkflow, Workflow |
Version | 1.16.0 |
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 | |
LinkingTo | |
Suggests | knitr, rmarkdown, BiocStyle |
SystemRequirements | |
Enhances | |
URL | https://f1000research.com/articles/5-1408/v3 |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me |
Follow Installation instructions to use this package in your R session.
Source Package | RNAseq123_1.16.0.tar.gz |
Windows Binary | |
macOS 10.13 (High Sierra) | |
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/ |
Package Downloads Report | Download Stats |
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