Pathview: An R package for pathway based data integration and visualization (original) (raw)

Assume R has been correctly installed and accessible under current directory. Otherwise, please contact your system admin or follow the instructions on R website and Bioconductor website. Here I would strongly recommend users to install or upgrade to the latest verison of R (>=3.0)/Bioconductor (>=2.12) for simpler installation and better use of Pathview. You may need to update your biocLite function too if you upgrade R/Biocondutor under Windows.

Start R: from Linux/Unix command line, type in "R (Enter)"; for Mac or Windows GUI, double click the R application icon to enter R console.

End R: type in "q() (Enter)" when you are finished using R, but not now.

Two options to install pathview package are demonstrated here.

Simple way: install with Bioconductor installation script biocLite directly (this included all dependencies automatically too):

> source("http://bioconductor.org/biocLite.R")
> biocLite("pathview")

Or a bit more complexer: install manually, but require dependence packages to be installed using Bioconductor first:

> source("http://bioconductor.org/biocLite.R")
> biocLite(c("Rgraphviz", "png", "KEGGgraph", "org.Hs.eg.db"))

Then install pathview through R-forge: (R-forge installation may have problems sometimes.)

> install.packages("pathview",repos="http://R-Forge.R-project.org")

OR install manually: checkout or download pathview package (from Bioconductor, make sure with proper version number and zip format) and save to /your/local/directory/. This way you may install the latest updates on pathview (potentially without update the whole Bioconductor) by checking out the development version.

> install.packages("/your/local/directory/pathview_1.0.0.tar.gz", 
         repos = NULL, type = "source")

Note that there might be problems when installing Rgraphviz or XML (KEGGgraph dependency) package with outdated R/Biocondutor. Rgraphviz installation is a bit complicate with R 2.5 (Biocondutor 2.10) or earlier versions. Please check this Readme file on Rgraphviz. On Windows systems,XML frequently needs to be installed manually. Its windows binary can be downloaded from CRAN (http://cran.r-project.org/web/packages/XML/index.html) and then:

> install.packages("/your/local/directory/XML_3.95-0.2.zip", repos = NULL)