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This is the development version of rnaseqGene; for the stable release version, see rnaseqGene.

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

Bioconductor version: Development (3.20)

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>

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


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


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:

RNA-seq workflow at the gene level HTML R Script


biocViews GeneExpressionWorkflow, ImmunoOncologyWorkflow, Workflow
Version 1.29.0
License Artistic-2.0
Depends R (>= 3.3.0), BiocStyle, airway(>= 1.5.3), tximeta, magrittr, DESeq2, apeglm, vsn, dplyr, ggplot2, hexbin, pheatmap, RColorBrewer, PoiClaClu, glmpca, ggbeeswarm, genefilter, AnnotationDbi,, Gviz, sva, RUVSeq, fission
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