Using Bioconductor

The current release of Bioconductor is version 3.4; it works with R version 3.3.1. Users of older R and Bioconductor users must update their installation to take advantage of new features and to access packages that have been added to Bioconductor since the last release.

Install the latest release of R, then get the latest version of Bioconductor by starting R and entering the commands

## try http:// if https:// URLs are not supported

Details, including instructions to install additional packages and to update, find, and troubleshoot are provided below. A devel version of Bioconductor is available. There are good reasons for using biocLite() for managing Bioconductor resources.

Install R

  1. Download the most recent version of R. The R FAQs 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).
  1. 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.

  2. 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.

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Install Bioconductor Packages

Use the biocLite.R script to install Bioconductor packages. To install core packages, type the following in an R command window:

## try http:// if https:// URLs are not supported

Install specific packages, e.g., “GenomicFeatures” and “AnnotationDbi”, with

biocLite(c("GenomicFeatures", "AnnotationDbi"))

The biocLite() function (in the BiocInstaller package installed by the biocLite.R script) has arguments that change its default behavior; type ?biocLite for further help.

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Find Bioconductor Packages

Visit the Workflows page and software package list to discover available packages.

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Update Installed Bioconductor Packages

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

## try http:// if https:// URLs are not supported
biocLite()                  ## R version 3.0 or later

Use the argument ask=FALSE to update old packages without being prompted. For older versions of R, use the command biocLite(NULL). Read the help page for ?biocLite for additional details.

Upgrading installed Bioconductor packages

Some versions of R support more than one version of Bioconductor. To use the latest version of Bioconductor for your version of R, enter

## try http:// if https:// URLs are not supported
biocLite("BiocUpgrade")     ## R version 2.15 or later

Read the help page for ?BiocUpgrade for additional details. Remember that more recent versions of Bioconductor may be available if your version of R is out-of-date.

For more detail on Bioconductor approaches to versioning, see the newsletter and version numbering developer reference.

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

## try http:// if https:// URLs are not supported
pkgs <- rownames(installed.packages())
biocLite(pkgs, type="source")

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. It also requires that you have the necessary compilers installed.

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Troubleshoot Package Installations

Use the commands

biocValid()             ## R version 3.0 or later

to flag packages that are either out-of-date or too new for your version of Bioconductor. The output suggests ways to solve identified problems, and the help page ?biocValid lists arguments influencing the behavior of the function.

Troubleshoot BiocInstaller

If you see a message like this:

BiocInstaller version 3.2 is too old for R version 3.3

…do the following:

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Why Use biocLite()?

biocLite() is the recommended way to install Bioconductor packages. There are several reasons for preferring this to the ‘standard’ way in which R pacakges are installed via install.packages().

Bioconductor has a repository and release schedule that differs from R (Bioconductor has a ‘devel’ branch to which new packages and updates are introduced, and a stable ‘release’ branch emitted once every 6 months to which bug fixes but not new features are introduced).

A consequence of the mismatch between R and Bioconductor release schedules is that the Bioconductor version identified by install.packages() is sometimes not the most recent ‘release’ available. For instance, an R minor version may be introduced some months before the next Bioc release. After the Bioc release the users of the R minor version will be pointed to an out-of-date version of Bioconductor.

A consequence of the distinct ‘devel’ branch is that install.packages() sometimes points only to the ‘release’ repository, whereas Bioconductor developers and users wanting leading-edge features wish to access the Bioconductor ‘devel’ repository. For instance, the Bioconductor 3.0 release is available for R.3.1.x, so Bioconductor developers and leading-edge users need to be able to install the devel version of Bioconductor packages into the same version (though perhaps different instance or at least library location) of R that supports version 2.14 of Bioconductor.

An indirect consequence of Bioconductor’s structured release is that packages generally have more extensive dependencies with one another, both explicitly via the usual package mechanisms and implicitly because the repository, release structure, and Bioconductor community interactions favor re-use of data representations and analysis concepts across packages. There is thus a higher premium on knowing that packages are from the same release, and that all packages are current within the release.

These days, the main purpose of source("") is to install and attach the ‘BiocInstaller’ package.

In a new installation, the script installs the most recent version of the BiocInstaller package relevant to the version of R in use, regardless of the relative times of R and Bioconductor release cycles. The BiocInstaller package serves as the primary way to identify the version of Bioconductor in use

> library(BiocInstaller)
Bioconductor version 2.14 (BiocInstaller 1.14.2), ?biocLite for help

Since new features are often appealing to users, but at the same time require an updated version of Bioconductor, the source() command evaluated in an out-of-date R will nudge users to upgrade, e.g., in R-2.15.3

> source("")
A new version of Bioconductor is available after installing the most
  recent version of R; see

The biocLite() function is provided by BiocInstaller. This is a wrapper around install.packages, but with the repository chosen according to the version of Bioconductor in use, rather than to the version relevant at the time of the release of R.

biocLite() also nudges users to remain current within a release, by default checking for out-of-date packages and asking if the user would like to update

> biocLite()
Using Bioconductor version 2.14 (BiocInstaller 1.14.2), R version
Old packages: 'BBmisc', 'genefilter', 'GenomicAlignments',
  'GenomicRanges', 'IRanges', 'MASS', 'reshape2', 'Rgraphviz',
  'RJSONIO', 'rtracklayer'
Update all/some/none? [a/s/n]:

The BiocInstaller package provides facilities for switching to the ‘devel’ version of Bioconductor

> BiocInstaller::useDevel()
Installing package into ‘/home/mtmorgan/R/x86_64-unknown-linux-gnu-library/3.1’
(as ‘lib’ is unspecified)
trying URL ''
Content type 'application/x-gzip' length 14144 bytes (13 Kb)
opened URL
downloaded 13 Kb

* installing *source* package ‘BiocInstaller’ ...
Bioconductor version 3.0 (BiocInstaller 1.15.5), ?biocLite for help
'BiocInstaller' changed to version 1.15.5

(at some points in the R / Bioconductor release cycle use of ‘devel’ requires use of a different version of R itself, in which case the attempt to useDevel() fails with an appropriate message).

The BiocInstaller package also provides biocValid() to test that the installed packages are not a hodgepodge from different Bioconductor releases (the ‘too new’ packages have been installed from source rather than a repository; regular users would seldom have these).

> biocValid()

* sessionInfo()

R version 3.1.0 Patched (2014-05-06 r65533)
Platform: x86_64-unknown-linux-gnu (64-bit)

* Out-of-date packages
update with biocLite()

* Packages too new for Bioconductor version '3.0'
downgrade with biocLite(c("ShortRead", "BatchJobs"))

Error: 9 package(s) out of date; 2 package(s) too new

For users who spend a lot of time in Bioconductor, the features outlined above become increasingly important and biocLite() is much preferred to install.packages().

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Pre-configured Bioconductor

Bioconductor is also available as a set of Amazon Machine Images (AMIs) and Docker images.

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Packages »

Bioconductor's stable, semi-annual release:

Bioconductor is also available via Docker and Amazon Machine Images.

Documentation »


R / CRAN packages and documentation