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Fero Lab Custom R packages
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Install R on your computer:
The following custom packages may be used with R statistical software and Bioconductor packages to analyze array data. Before being able to use them you will need to install R on your computer.
R homepage
Everything you wanted to know about R but were afraid to ask.
R download and Installation
From the FHCRC mirror
Bioconductor homepage
Packages and vinettes from Bionconductor are available here or may be downloaded from within the R program.
Download custom packages and instructions:
Use the following links to download or learn more about our custom R source packages. Instructions for installing the packages are also given, below.
ArrayFun: A package to analyze 2-color expression arrays (cDNA or oligonucleotide) starting with raw (.gpr) data. Includes layout data for the FHCRC murine 15k, and 22k cDNA arrays obviating the need for GAL files on these platforms.
BACarray: A package to analyze CGH arrays (2-color arrays) starting with raw data (.gpr files). Includes layout data from the FHCRC human BAC array.
HomoVert: A package to convert Entrez Gene IDs from one species to another. It has a builtin Homologene conversion table and a function to convert your Gene IDs to a second species of your choice. Also outputs gene symbol, protein ID and protein accession numbers.
Install custom packages:
Install and launch R.app (See R download and Installation, above).
Download one of the Custom Packages, above, (e.g. 'ArrayFun') to your home folder.
Mac OS (using R.app)
From within R.app select:
Packages & Data > Package Installer
From the Installer window choose:
Packages Repository > Local Source Package
Install... (browse to the Source package in your home folder.)
Using Linux, Mac OS Terminal or Mac OS X11:
Type:
R CMD Install ArrayFun_x.y.tar.gz
If you get an error 'Error: object "R" not found' then you have not installed R correctly (e.g. it has not been added to your path).
Once the process is complete you will see the message: "DONE (Package name)".
Using Windows:
Installing source packages under Windows is possible but requires extra software tools. See the R for Windows FAQ for more information. If you know an R programmer who uses Windows you could ask him or her to compile the package and give you the resulting binary file which should be easier to install.
Using custom packages:
1. Launch R.app (Mac OS)
(Alternatively type R in an X11 window. The Mac OS Terminal application can also be used but it lacks the ability to produce on-screen graphics)
2. Into the console type:
library(ArrayFun) # or one of the other Packages
3. For information you can either:
a. See one of the PDF manual above,
b. Type ?ArrayFun into the console, or
c. Type ArrayFun into the search field at the top of the R.app window.
For questions or suggestions contact: Matthew Fero
