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Bioconductor is an open source and open development software project
for the analysis and comprehension of genomic data.

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Installation Instructions

Install R

  1. Download the most recent version of R from The Comprehensive R Archive Network (CRAN). The R FAQ and the R Installation and Administration Manual contain detailed instructions for installing R on various platforms (Linux, OS X, and Windows being the main ones).
  2. Start the R program; on Windows and OS X, this will usually mean double-clicking on the R application, on UNIX-like systems, type "R" at a shell prompt.
  3. As a first step with R, start the R help browser by typing "help.start()" in the R command window. For help on any function, e.g. the "mean" function, type "? mean".

Install standard Bioconductor packages

Install BioConductor packages using the biocLite.R installation script. In an R command window, type the following:

source("http://bioconductor.org/biocLite.R")
biocLite()

This installs the following packages: affy, affydata, affyPLM, annaffy, annotate, Biobase, Biostrings, DynDoc, gcrma, genefilter, geneplotter, hgu95av2.db, limma, marray, matchprobes, multtest, ROC, vsn, xtable, affyQCReport. After downloading and installing these packages, the script prints "Installation complete" and TRUE.

The biocLite script has arguments that change the default behavior:

pkgs
Character vector of BioConductor packages to install.
destdir
File system directory for downloaded packages.
lib
R library where packages are installed.

Install additional Bioconductor packages

There are many Bioconductor and R packages in addition to those in the default installation of biocLite. A catalog of the Bioconductor packages is available at BiocViews. To install a new package, e.g., EBImage, use

source("http://bioconductor.org/biocLite.R")
biocLite("EBImage")

Install "pkg1" and "pkg2" with

biocLite(c("pkg1", "pkg2"))

Install package groups

In special circumstances, a particular predefined group of packages can be installed. The following groups are available:

default
This defines the packages that are installed when biocLite is invoked with no additional arguments.
lite
Essential packages for very low-bandwidth connections.
affy
A selection of packages particularly useful in analysis of Affymetrix expression arrays.
graph
Packages useful for graph-based algorithms and representations.
monograph
Packages for use with the book Bioinformatics and Computational Biology Solutions Using R and Bioconductor.
RBioinf
Packages for use with the book Bioinformatics with R.
all
All software packages; this is a very large installation and not recommended for most users.

To install a group of packages, use a command such as

biocLite(groupName="RBioinf")

Update installed Bioconductor packages

Bioconductor packages, especially those in the development branch, are updated fairly regularly. To identify packages requiring update, start a new session of R and enter

source("http://bioconductor.org/biocLite.R")
old.packages(repos=biocinstallRepos())
To update all installed packages that are out of date, start a new session of R and enter

source("http://bioconductor.org/biocLite.R")
update.packages(repos=biocinstallRepos(), ask=FALSE)

Read the help page for update.packages for additional details.

Recompiling installed Bioconductor packages

Rarely, underlying changes in the operating system require ALL installed packages to be recompiled for source (C or Fortran) compatibility. One way to address this might be to start a new R session and enter

source("http://bioconductor.org/biocLite.R")
pkgs <- rownames(installed.packages())
biocLite(pkgs)

As this will reinstall all currently installed packages, it likely involves a significant amount of network bandwidth and compilation time. All packages are implicitly updated, and the cumulative effect might introduce wrinkles that disrupt your work flow.

Additional resources

News
2009-10-26

BioC 2.5, consisting of 352 packages and designed to work with R 2.10.z, was released today.

2009-01-07

R, the open source platform used by Bioconductor, featured in a series of articles in the New York Times.