maEndToEnd

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

An end to end workflow for differential gene expression using Affymetrix microarrays


Bioconductor version: 3.16

In this article, we walk through an end-to-end Affymetrix microarray differential expression workflow using Bioconductor packages. This workflow is directly applicable to current "Gene" type arrays, e.g. the HuGene or MoGene arrays, but can easily be adapted to similar platforms. The data analyzed here is a typical clinical microarray data set that compares inflamed and non-inflamed colon tissue in two disease subtypes. For each disease, the differential gene expression between inflamed- and non-inflamed colon tissue was analyzed. We will start from the raw data CEL files, show how to import them into a Bioconductor ExpressionSet, perform quality control and normalization and finally differential gene expression (DE) analysis, followed by some enrichment analysis.

Author: Bernd Klaus [aut], Stefanie Reisenauer [aut, cre]

Maintainer: Stefanie Reisenauer <steffi.reisenauer at tum.de>

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

Installation

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


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

BiocManager::install("maEndToEnd")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

Details

biocViews GeneExpressionWorkflow, Workflow
Version 2.18.0
License MIT + file LICENSE
Depends R (>= 3.5.0), Biobase, oligoClasses, ArrayExpress, pd.hugene.1.0.st.v1, hugene10sttranscriptcluster.db, oligo, arrayQualityMetrics, limma, topGO, ReactomePA, clusterProfiler, gplots, ggplot2, geneplotter, pheatmap, RColorBrewer, dplyr, tidyr, stringr, matrixStats, genefilter, openxlsx, Rgraphviz, enrichplot
Imports
System Requirements
URL https://www.bioconductor.org/help/workflows/
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Suggests BiocStyle, knitr, devtools, rmarkdown
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/maEndToEnd
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/maEndToEnd
Package Short Url https://bioconductor.org/packages/maEndToEnd/
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