RnaSeqGeneEdgeRQL

DOI: 10.18129/B9.bioc.RnaSeqGeneEdgeRQL  

This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see RnaSeqGeneEdgeRQL.

Gene-level RNA-seq differential expression and pathway analysis using Rsubread and the edgeR quasi-likelihood pipeline

Bioconductor version: 3.16

This workflow package provides, through its vignette, a complete case study analysis of an RNA-Seq experiment using the Rsubread and edgeR packages. The workflow starts from read alignment and continues on to data exploration, to differential expression and, finally, to pathway analysis. The analysis includes publication quality plots, GO and KEGG analyses, and the analysis of a expression signature as generated by a prior experiment.

Author: Yunshun Chen, Aaron Lun, Gordon Smyth

Maintainer: Yunshun Chen <yuchen at wehi.edu.au>

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

Installation

To install this package, start R (version "4.2") and enter:

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

BiocManager::install("RnaSeqGeneEdgeRQL")

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("RnaSeqGeneEdgeRQL")

 

HTML R Script From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline

Details

biocViews GeneExpressionWorkflow, ImmunoOncologyWorkflow, Workflow
Version 1.22.0
License Artistic-2.0
Depends R (>= 3.3.0), edgeR, gplots, org.Mm.eg.db, GO.db, BiocStyle
Imports
LinkingTo
Suggests knitr, knitcitations, rmarkdown
SystemRequirements
Enhances
URL http://f1000research.com/articles/5-1438
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 RnaSeqGeneEdgeRQL_1.22.0.tar.gz
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/RnaSeqGeneEdgeRQL
Source Repository (Developer Access) git clone [email protected]:packages/RnaSeqGeneEdgeRQL
Package Short Url https://bioconductor.org/packages/RnaSeqGeneEdgeRQL/
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