Upgrade R Environment/Libraries (Mac OSX) without a Disruption of the Present CRAN and Bioconductor Infrastructure
Upgrade R Environment/Libraries (Mac OSX) without a Disruption of the Present CRAN and Bioconductor Infrastructure R programming language and many of its packages are under continuous development, with frequent major releases happening several times in a year. For computational biologists/developers, the best practice is to work on the most up-to-date version of R, so that the code would benefit from the increased execution performance and robustness. Starting from the latest version of R would also assure the absence of the usage of obsolete language features. However, as of now, a magical command that would simply upgrade your whole R environment into both the latest version of R and the latest versions of installed libraries, does not exist. During the course of the usage of the R environment, you would certainly accumulate/install many add-on libraries, the continuous presence of which could be vital for your projects. Here, I describe a way of ...