Workflow Package: rnaseqGene

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

Bioconductor version: 3.7

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>

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("rnaseqGene")

Documentation

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

browseVignettes("rnaseqGene")

 

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R Script

RNA-seq workflow at the gene level

Details

biocViews	GeneExpressionWorkflow, Workflow
Version	1.2.0
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/
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