Use the BiocManager package to install and manage packages from the Bioconductor project for the statistical analysis and comprehension of high-throughput genomic data.
Current Bioconductor packages are available on a ‘release’ version intended for every-day use, and a ‘devel’ version where new features are introduced. A new release version is created every six months. Using the BiocManager package helps users install packages from the same release.
Use standard R installation procedures to install the BiocManager package. This command is requried only once per R installation.
Install Bioconductor (or CRAN) packages with
Installed packages can be updated to their current version with
CRAN packages for out-of-date Bioconductor releases can be
installed from the Microsoft R
Application Network or RStudio
Package Manager; see
?BiocManager.snapshot to change
version() to discover the version of
Bioconductor currently in use.
Bioconductor packages work best when they are all from the
same release. Use
valid() to identify packages that are
out-of-date or from unexpected versions.
valid() returns an object that can be queried for
detailed information about invalid packages, as illustrated in the
following screen capture
> v <- valid() Warning message: 6 packages out-of-date; 0 packages too new > names(v)  "out_of_date" "too_new" > head(v$out_of_date, 2) Package LibPath bit "bit" "/home/mtmorgan/R/x86_64-pc-linux-gnu-library/3.5-Bioc-3.8" ff "ff" "/home/mtmorgan/R/x86_64-pc-linux-gnu-library/3.5-Bioc-3.8" Installed Built ReposVer Repository bit "1.1-12" "3.5.0" "1.1-13" "https://cloud.r-project.org/src/contrib" ff "2.2-13" "3.5.0" "2.2-14" "https://cloud.r-project.org/src/contrib" >
Packages available for your version of Bioconductor can be
available(); the first argument can be used
to filter package names based on a regular expression, e.g., ‘BSgenome’
package available for Homo sapiens
avail <- BiocManager::available() length(avail) # all CRAN & Bioconductor packages BiocManager::available("BSgenome.Hsapiens") # BSgenome.Hsapiens.* packages
Questions about installing and managing Bioconductor packages should be addressed to the Bioconductor support site.
After updating R (e.g., from R version 3.5.x to
R version 3.6.x at the time of writing this) and trying to load
BiocManager, R replies
Error: .onLoad failed in loadNamespace() for 'BiocManager', details: call: NULL error: Bioconductor version '3.8' requires R version '3.5'; see https://bioconductor.org/install
This problem arises because
BiocManager uses a second
BiocVersion, to indicate the version of
Bioconductor in use. In the original installation,
BiocManager had installed
appropriate for R version 3.5. With the update, the version of
Bioconductor indicated by
BiocVersion is no longer
valid – you’ll need to update
BiocVersion and all
Bioconductor packages to the most recent version available for
your new version of R.
The recommended practice is to maintain a separate library for each R and Bioconductor version. So instead of installing packages into R’s system library (e.g., as ‘administrator’), install only base R into the system location. Then use aliases or other approaches to create R / Bioconductor version-specific installations. This is described in the section on maintaining multiple versions of R and Bioconductor.
Alternatively, one could update all Bioconductor packages in
the previous installation directory. The problem with this is that the
previous version of Bioconductor is removed, compromising the
ability to reproduce earlier results. Update all Bioconductor
packages in the previous installation directory by removing all
remove.packages("BiocVersion") # repeat until all instances removed
Then install the updated
BiocVersion, and update all
Bioconductor packages; answer ‘yes’ when you are asked to
update a potentially large number of Bioconductor packages.
Confirm that the updated Bioconductor is valid for your version of R
Large packages can take a long time to downloaded over poor internet
connects. The BiocManager package sets the time limit to 300 seconds,
options(timeout = 300). Only part of a package may
download, e.g., only 15.1 of 79.4 MB in the example below
trying URL 'https://bioconductor.org/packages/3.12/data/annotation/src/contrib/org.Hs.eg.db_3.12.0.tar.gz' Content type 'application/x-gzip' length 83225518 bytes (79.4 MB) ========= downloaded 15.1 MB
or perhaps with a warning (often difficult to see in the output)
Error in download.file(url, destfile, method, mode = "wb", ...) : ... ...: Timeout of 300 seconds was reached ...
Try increasing the download timeout, e.g,
options(timeout = 600).
version= argument to update all packages to a
specific Bioconductor version
Bioconductor versions are associated with specific R versions, as summarized here. Attempting to install a version of Bioconductor that is not supported by the version of R in use leads to an error; using the most recent version of Bioconductor may require installing a new version of R.
> BiocManager::install(version="3.9") Error: Bioconductor version '3.9' requires R version '3.6'; see https://bioconductor.org/install
A special version,
version="devel", allows use of
Bioconductor packages that are under development.
It is possible to have multiple versions of Bioconductor installed on the same computer. A best practice is to create an initial R installation. Then create and use a library for each version of Bioconductor. The library will contain all Bioconductor, CRAN, and other packages for that version of Bioconductor. We illustrate the process assuming use of Bioconductor version 3.7, available using R version 3.5
Create a directory to contain the library (replace
USER_NAME with your user name on Windows)
Set the environment variable
R_LIBS_USER to this
directory, and invoke R. Command line examples for Linux
cmd /C "set R_LIBS_USER=C:\Users\USER_NAME\Documents\R\3.5-Bioc-3.7 && R"
Once in R, confirm that the version-specific library path has been set
On Linux and macOS, create a bash alias to save typing, e.g.,
alias Bioc3.7='R_LIBS_USER=~/R/3.5-Bioc-3.7 R'
alias Bioc3.7='R_LIBS_USER=~/Library/R/3.5-Bioc-3.7/library R'
Invoke these from the command line as
On Windows, create a shortcut. Go to My Computer and navigate to a directory that is in your PATH. Then right-click and choose New->Shortcut. In the “type the location of the item” box, put:
cmd /C "set R_LIBS_USER=C:\Users\USER_NAME\Documents\R\3.5-Bioc-3.7 && R"
Click “Next”. In the “Type a name for this shortcut” box, type
BiocManager expects to be able to connect to online Bioconductor and CRAN repositories. Off-line use generally requires the following steps.
rsync to create local repositories of CRAN and Bioconductor.
Tell R about these repositories using (e.g., in a site-wide
options( repos = c(CRAN_mirror = "file:///path/to/CRAN-mirror"), BioC_mirror = "file:///path/to/Bioc-mirror" )
Validate repository setting by reviewing the output of
Create an environment variable or option, e.g.,
options( BIOCONDUCTOR_ONLINE_VERSION_DIAGNOSIS = FALSE )
install.packages() to bootstrap the BiocManager
BiocManager can then be used for subsequent installations, e.g.,
BiocManager also expects to reference an online
configuration yaml file for Bioconductor version validation at https://bioconductor.org/config.yaml. With offline use,
users are expected to either host this file locally or provide their
config.yaml version. The package allows either an
environment variable or R-specific option to locate this file, e.g.,
```r options( BIOCONDUCTOR_CONFIG_FILE = "file:///path/to/config.yaml" ) ```
BiocManager’s job is to make sure that all packages are installed from the same Bioconductor version, using compatible R and CRAN packages. However, R has an annual release cycle, whereas Bioconductor has a twice-yearly release cycle. Also, Bioconductor has a ‘devel’ branch where new packages and features are introduced, and a ‘release’ branch where bug fixes and relative stability are important; CRAN packages do not distinguish between devel and release branches.
In the past, one would install a Bioconductor package by
evaluating the command
read a file from the web. The file contained an installation script that
was smart enough to figure out what version of R and
Bioconductor were in use or appropriate for the person invoking
the script. Sourcing an executable script from the web is an obvious
Our solution is to use a CRAN package BiocManager, so that users install from pre-configured CRAN mirrors rather than typing in a URL and sourcing from the web.
But how does a CRAN package know what version of Bioconductor is in use? Can we use BiocManager? No, because we don’t have enough control over the version of BiocManager available on CRAN, e.g., everyone using the same version of R would get the same version of BiocManager and hence of Bioconductor. But there are two Bioconductor versions per R version, so that does not work!
BiocManager could write information to a cache on the user disk, but this is not a robust solution for a number of reasons. Is there any other way that R could keep track of version information? Yes, by installing a Bioconductor package (BiocVersion) whose sole purpose is to indicate the version of Bioconductor in use.
By default, BiocManager installs the BiocVersion package
corresponding to the most recent released version of
Bioconductor for the version of R in use. At the time
this section was written, the most recent version of R is R-3.6.1,
associated with Bioconductor release version 3.9. Hence on
first use of
BiocManager::install() we see BiocVersion
version 3.9.0 being installed.
> BiocManager::install() Bioconductor version 3.9 (BiocManager 1.30.4), R 3.6.1 Patched (2019-07-06 r76792) Installing package(s) 'BiocVersion' trying URL 'https://bioconductor.org/packages/3.9/bioc/src/contrib/\ BiocVersion_3.9.0.tar.gz' ...
Requesting a specific version of Bioconductor updates, if possible, the BiocVersion package.
> ## 3.10 is available for R-3.6 > BiocManager::install(version="3.10") Upgrade 3 packages to Bioconductor version '3.10'? [y/n]: y Bioconductor version 3.10 (BiocManager 1.30.4), R 3.6.1 Patched (2019-07-06 r76792) Installing package(s) 'BiocVersion' trying URL 'https://bioconductor.org/packages/3.10/bioc/src/contrib/\ BiocVersion_3.10.1.tar.gz' ... > ## back down again... > BiocManager::install(version="3.9") Downgrade 3 packages to Bioconductor version '3.9'? [y/n]: y Bioconductor version 3.9 (BiocManager 1.30.4), R 3.6.1 Patched (2019-07-06 r76792) Installing package(s) 'BiocVersion' trying URL 'https://bioconductor.org/packages/3.9/bioc/src/contrib/\ BiocVersion_3.9.0.tar.gz' ...
n to the prompt to up- or downgrade packages
leaves the installation unchanged, since this would immediately create
an inconsistent installation.
One potential problem occurs when there are two or more
.libPaths(), with more than one BiocVersion package
installed. This might occur for instance if a ‘system administrator’
installed BiocVersion, and then a user installed their own version. In
this circumstance, it seems appropriate to standardize the installation
by repeatedly calling
all versions are removed, and then installing the desired version.
When the Bioconductor version cannot be obtained from the version map hosted at https://bioconductor.org/config.yaml, this error will occur. It may be a result of poor internet connectivity or offline use. See the offline config.yaml section above.
Usually occurs when the map is unable to be downloaded possibly due
to a missing
BIOCONDUCTOR_CONFIG_FILE. For offline use, a
copy of the configuration file should be downloaded and its address set
to the environment variable or option.
On rare occasion, the version map hosted at https://bioconductor.org/config.yaml may be misconfigured. The check ensures that all the version name tags, i.e., out-of-date, release, devel, and future are in the map.
The type input refers to the version name inputs, mainly release and devel. This error is chiefly due to internal logic and is not due to user error. Please open an issue on the GitHub issues page.
## R Under development (unstable) (2023-02-12 r83801) ## Platform: x86_64-pc-linux-gnu (64-bit) ## Running under: Ubuntu 22.04.2 LTS ## ## Matrix products: default ## BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0 ## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0 ## ## locale: ##  LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C ##  LC_TIME=en_US.UTF-8 LC_COLLATE=C ##  LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 ##  LC_PAPER=en_US.UTF-8 LC_NAME=C ##  LC_ADDRESS=C LC_TELEPHONE=C ##  LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C ## ## time zone: America/New_York ## tzcode source: system (glibc) ## ## attached base packages: ##  stats graphics grDevices utils datasets methods base ## ## loaded via a namespace (and not attached): ##  digest_0.6.29 R6_2.5.1 fastmap_1.1.0 xfun_0.33 ##  magrittr_2.0.3 cachem_1.0.6 stringr_1.4.1 knitr_1.40 ##  htmltools_0.5.3 rmarkdown_2.17 cli_3.4.1 sass_0.4.2 ##  jquerylib_0.1.4 compiler_4.3.0 tools_4.3.0 evaluate_0.17 ##  bslib_0.4.0 yaml_2.3.5 rlang_1.0.6 jsonlite_1.8.2 ##  stringi_1.7.8