rnaseqGene

DOI: 10.18129/B9.bioc.rnaseqGene    

This package is for version 3.9 of Bioconductor; for the stable, up-to-date release version, see rnaseqGene.

RNA-seq workflow: gene-level exploratory analysis and differential expression

Bioconductor version: 3.9

Here we walk through an end-to-end gene-level RNA-seq differential expression workflow using Bioconductor packages. We will start from the FASTQ files, show how these were aligned to the reference genome, and prepare a count matrix which tallies the number of RNA-seq reads/fragments within each gene for each sample. We will perform exploratory data analysis (EDA) for quality assessment and to explore the relationship between samples, perform differential gene expression analysis, and visually explore the results.

Author: Michael Love [aut, cre]

Maintainer: Michael Love <michaelisaiahlove at gmail.com>

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

Installation

To install this package, start R (version "3.6") and enter:

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

BiocManager::install("rnaseqGene")

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("rnaseqGene")

 

HTML R Script RNA-seq workflow at the gene level

Details

biocViews GeneExpressionWorkflow, ImmunoOncologyWorkflow, Workflow
Version 1.8.0
License Artistic-2.0
Depends R (>= 3.3.0), BiocStyle, airway, Rsamtools, GenomicFeatures, GenomicAlignments, BiocParallel, magrittr, DESeq2, apeglm, vsn, dplyr, ggplot2, pheatmap, RColorBrewer, PoiClaClu, ggbeeswarm, genefilter, AnnotationDbi, org.Hs.eg.db, ReportingTools, Gviz, sva, RUVSeq, fission
Imports
LinkingTo
Suggests knitr, rmarkdown
SystemRequirements
Enhances
URL https://github.com/mikelove/rnaseqGene/
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 rnaseqGene_1.8.0.tar.gz
Windows Binary
Mac OS X 10.11 (El Capitan)
Source Repository git clone https://git.bioconductor.org/packages/rnaseqGene
Source Repository (Developer Access) git clone [email protected]:packages/rnaseqGene
Package Short Url https://bioconductor.org/packages/rnaseqGene/
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