R 2.14.0 is released!

The new R 2.14.0 is out! Get the source code from here.

Take a look at these posts for some miscellaneous advices to make the upgrade easier.

Also this thread on stackoverflow and this post contributed by Tal Galili can be of some value to make the procedure less painful.

Feel free to contribute with suggestions about how to upgrade your R installation.

Installing Multiple Version of R in parallel on the same machine - Mac OS X

In a few days I'm going to attend a Bioconductor Course; I was requested to install on my MacBook (Mac OS X 10.5.8) a developer version of R (plus ad hoc Bioconductor packages). In order to keep my old R installation ((2.13) along side the new one (2.14) I decided to use the RSwitch app (you can download from here) and the instructions you can read here.
In practical term, you type the following commands in Terminal:

sudo pkgutil --forget org.r-project.R.Leopard.fw.pkg
sudo pkgutil --forget org.r-project.R.Leopard.GUI.pkg
sudo pkgutil --forget org.r-project.R.Leopard.GUI64.pkg

You install the alternative version of R (for example, following the procedure depicted here) and then you can switch between the different version using the RSwitch GUI (see the below screenshot). So easy!

R Upgrade on Mac Os X 10.5.5 (Leopard)

To reinstall packages from an old version of R to a new one.
In the old version type:
tmp <- installed.packages()
installedpkgs <- as.vector(tmp[is.na(tmp[,"Priority"]), 1])
save(installedpkgs, file="installed_old.rda")
Install the most recent version of R:
Download the most recent version of R from The Comprehensive R Archive Network (CRAN)
# To wipe the old R version
rm -rf /Library/Frameworks/R.framework /Applications/R.app
rm -rf /Library/Receipts/R-*
Build from source new R version (see this FAQ).
From inside the decompressed R-?.?.? directory type:
# See Section 2.2 of RMacOSX FAQ for the flag description
./configure --with-blas='-framework vecLib' --enable-BLAS-shlib
make
sudo make install
Install BioConductor packages using the biocLite.R installation script.
In an R command window, type the following:
source("http://bioconductor.org/biocLite.R")
chooseBioCmirror()
biocLite()
If you have other Bioconductor packages missing from the old installation:

load("installed_old.rda")
tmp <- installed.packages()
installedpkgs.new <- as.vector(tmp[is.na(tmp[,"Priority"]), 1])
missing <- setdiff(installedpkgs, installedpkgs.new)
for (i in 1:length(missing)) biocLite(missing[i])
Re-install the missing packages from CRAN:
load("installed_old.rda")
tmp <- installed.packages()
installedpkgs.new <- as.vector(tmp[is.na(tmp[,"Priority"]), 1])
missing <- setdiff(installedpkgs, installedpkgs.new)
install.packages(missing)
update.packages()
If you use some package created by Henrik Bengtsson:
source("http://www.braju.com/R/hbLite.R")
hbLite()
If you find your X11 broken after the installation procedure (it happens every time to me, at least on Leopard) install the XQuartz App from here.

Update: If you need to install a recent version of R on old hardware (Power PC G4) and OS (Mac OS X 10.4 here) this post can be useful.

R installing on Unix/Linux - no root access

Thanks and credit to Joern Toedling for this useful and clear how-to!

From The Bioconductor Digest, Vol 62, Issue 14:
You do not need to have root access to a machine to install your own
versions of R and your favourite packages there. This is how to do it:
1. downloaded the tar.gz of the development version of R from
ftp://ftp.stat.math.ethz.ch/Software/R/
2. uncompress it to a directory you have write access to, say ~/local/R
3. change into the uncompressed directory, ~/local/R/R-devel
4. run "./configure"
5. run "make"
Afterwards you can start R by executing ~/local/R/R-devel/bin/R;
to simplify that either add the bin directory to your path or create an alias for R
You do not need to run "make install" to work with R.
For packages,
1. create a directory in which you want the packages installed, e.g. ~/local/rpacks
2. create an evironment variable R_LIBS that holds the path to that directory, e.g. "setenv R_LIBS=${HOME}/local/rpacks" with that directory and a C-shell (use export with a Bash shell)
This environment variable tells R where to look first for installed packages and where to install packages when using "install.packages" or "biocLite".
R_LIBS is safe to use, since it only extends the path to look for packages and does not replace the default R library path.
I would recommend to add the alias for starting R and the R_LIBS
definition to your shell startup file (~/.cshrc or ~/.bashrc).