Once installed, the package must be loaded separately in every session with: library(matR).
Note that on the matR homepage, a pdf version of the manual is linked. With the package loaded in your R session, runtime help is available. For a list of topics, try the first command below. As usual in R, using ? gives help for individual functions, as shown.
help(package='matR')
?biomRequestNote that the executable tutorials posted on the matR homepage serve nicely as demos. Demos are also distributed with the package.
The first command below lists them, and the second runs a demo called "API".
demo(package='matR')
step.through('API')Simple instructions are given on the matR homepage. In case of trouble, here is detailed information and a more thorough procedure. matR makes liberal use of other R software packages. These “dependencies” should also be installed. matR and its dependencies are mostly available from CRAN (the Comprehensive R Archive Network), but some are only available from the Bioconductor repository. With the following commands, tell your R session where to look for those repositories. When prompted, select locations near you.
chooseCRANmirror(graphics=FALSE)
chooseBioCmirror(graphics=FALSE)Next, execute this command and select all the repositories listed:
setRepositories(graphics=FALSE)Then, the single command below should install matR and all its dependencies.
install.packages("matR", dependencies=TRUE)Difficulties may arise with packages that matR uses (“dependencies”). Third-party open-source software offers a wealth of functionality that can be leveraged to advantage, but often incurring costs in stability and portability. Addressing such issues is beyond the scope of this tutorial, but the maintainer of a problematic package should be able to help. Note that a missing dependency affects only the particular functionality it supports. So matR can always be used without all its dependencies installed.
Check out our Google group (matR-forum) for discussion and help.