Welcome to CAFE! =D
For news, click here
How to install CAFE depends on your operating system. System requirements are R 2.10 or up, although we recommend using the newest version of R, which is currently 3.0.1. Furthermore we recommend having adequate memory available, with 4 GB RAM being a workable minimum. It is advisable to have some kind of SWAP memory available, especially if you use the computer for other purposes as well.
If you use a Linux machine, you can simply download the
CAFE_x.x.x.x.tar.gz file. If you already have all dependencies - likely if you're an avid BioConductor user - you can simply type the following in a terminal:
$ R CMD INSTALL /path/to/CAFE/download
For Debian-based systems - Ubuntu, Linux Mint, Crunchbang etc - we provide an install script that automatically installs all dependencies. Download
CAFE_install_debain1.0.tar.gz, untar it, modify
cafeInstall.sh on line 11 to correct the path to where you downloaded CAFE, and run this same script afterwards.
Non-debian users can also run the
dependencies.R script to install all R dependencies, although this might exclude some CURL and XML packages that have to be installed on your system before.
For windows, you can download the
CAFE_x.x.x.x_WINDOWS.rar file. This contains 4 different CAFE builds, build for R 2.15 and R 3.0, with both the i386 and x86_64 architectures. Unpack the file, and install the correct build of CAFE for your system in RGui by:
packages --> install packages from local zip file(s) --> select the correct build. Before you can install CAFE, all dependencies (see below) must already have been installed. You can install these by doing the following in RGui
packages --> install packages.
The list of R dependencies is currently: biovizBase, GenomicRanges, IRanges, ggbio, affy, ggplot2, reshape2, annotate, grid, gridExtra, tcltk and Biobase
To see the package vignette, click here
An article describing CAFE is now in press in Bioinformatics.
Please cite the following if you have used CAFE:
Bollen, S., M. Leddin, M.A. Andrade-Navarro and N. Mah. 2014. CAFE: an R package for the detection of gross chromosomal abnormalities from gene expression microarray data. Bioinformatics. In press.