This is the released version of rnaseqGene; for the devel version, see rnaseqGene.
RNA-seq workflow: gene-level exploratory analysis and differential expressionBioconductor version: Release (3.21)
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, entercitation("rnaseqGene")
): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("rnaseqGene")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("rnaseqGene")
Details biocViews GeneExpressionWorkflow, ImmunoOncologyWorkflow, Workflow Version 1.32.0 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, org.Hs.eg.db, Gviz, sva, RUVSeq, fission Imports System Requirements URL https://github.com/thelovelab/rnaseqGene/ See More Suggests knitr, rmarkdown Linking To Enhances Depends On Me Imports Me Suggests Me Links To Me Package Archives
Follow Installation instructions to use this package in your R session.
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