Installation Instructions for MeV + R



  1. Introduction
  4. References



1. Introduction


The Bioconductor project is an open source software project that provides a wide range of statistical tools primarily based on the R programming environment and language. Taking advantage of R’s powerful statistical and graphical capabilities, developers have created and contributed numerous Bioconductor packages to solve a variety of data analysis needs. However, the use of these packages, requires a basic understanding of the R programming language. Our goal is to provide point-and-click access of these statistically powerful bioconductor packages to the biomedical community through the MeV environment. We have successfully integrated two Bioconductor packages, Rama and Bridge, in the MeV environment. RAMA (Robust Analysis of MicroArrays) [1] uses a Bayesian hierarchical model for the robust estimation of cDNA microarray intensities. BRIDGE (Bayesian Robust Inference for Differential Gene Expression) [2] tests for differentially expressed genes for both one and two-color microarray data. BRIDGE uses a similar Bayesian model as RAMA, but they are two independent bioconductor packages.

In order to make use of the MeV-R integrated environment, every computer that is used to run MeV-R needs the R Environment installed. Furthermore, Rama and Bridge are separate R packages that must be downloaded and installed from Bioconductor. Since MeV is an application written in Java, every computer running MeV-R needs to have the Java Run Time Environment installed. Alone, Java and R are independent environments and mutually ignorant of the other. In order to integrate MeV and R, we use Rserve, written by the University of Augsburg Institute for Mathematics, as the link between Java and R. Rserve is a TCP/IP server. Rserve must also be installed on every computer running MeV-R.

Having installed all the necessary components, the user will be required to start the Rserve server Win Mac each and every time he/she wants to do analysis using MeV-R.



Windows Users


Installing R/Rserve in Windows
  1. Download our R/Rserve installer
  2. Install by double clicking the downloaded installer.



Running Rserve in Windows
  1. Double click Rserve.exe to run it.


Updating Bioconductor packages in Windows
  1. Download the latest version of the package (devel) from Bioconductor
  2. Unzip the zipped file
  3. Replace the old rama or bridge directory with your new one. The location depends on where you installed R.
    By default it would be 'C:\Program Files\R\R-x.y.z\library'



Mac Users


Installing R in OS X (Precompiled Binary Version)
 This is the easiest way, but there is often a lag between when the latest version is available and when a precompiled binary is available.

  1. Download the Precompiled R Binary
  2. Install R by extracting the downloadeded .dmg file. A new volume will be mounted containing the installer. Run the installer by double clicking on
    R2.1.1...mpkg
    . You can place the Application anywhere you like, but the R framework is probably installed into
    /Libraries/Frameworks/R.framework/versions/x.y.z/resources.


Installing R in OS X (Build from Source)
You can update by simply installing the newer version of R. You do not have to uninstall previous versions.

  1. Download R.
    Note: Do NOT use a newer version as Rserve will NOT work with it.
  2. Be sure that the downloaded file is not in a folder containing a space in the name (like My Downloads) - It will not work. Open a terminal window and cd to the folder containing the file.
  3. Unpack it by typing 'tar zxvf R-2.4.1.tar.gz' (or whatever the filename is)
  4. CD into the unpacked directory (R-2.4.1 in this case). This directory should contain make and configure files.
  5. If you're using OS 10.4 (Tiger), issue the command 'sudo gcc_select 3.3' to force the use of gcc 3.3.
  6. Issue the command './configure'
  7. Issue the command 'make'
  8. Issue the command 'sudo chmod -R g+w /Library/Frameworks/R.framework' to change file permissions.
  9. Issue the command 'sudo make install'


Installing Rserve in OS X
  1. Download Rserve
  2. Open a terminal window and navigate to the directory containing the downloaded
    Rserve
    file. Type
    R CMD INSTALL Rserve_0.4-3.tar.gz


Updating Bioconductor packages in OS X (Command Line - RECOMMENDED)
  1. Download the latest version of the package (devel) from Bioconductor
  2. Open a Terminal window. This can be found at
    /Applications/Utilities/Terminal
    . Navigate to the downloaded file. For instance: if you downloaded the file to the desktop, type
    cd /Users/yourusername/Desktop
    and hit return. The prompt should now read
    MyComputer:~/Desktop username$
    To install the package, type
    R CMD INSTALL rama_1.4.0.tar.gz (or bridge_1.4.0.tar.gz)


Updating Bioconductor packages in OS X (Drag & Drop)

  1. Download the latest version of the package (devel) from Bioconductor
  2. Unpack the gzipped file.
  3. Replace the old rama directory with your new one in '/Library/Frameworks/R.framework/Versions/Current/Resources/library'

    Note: You may have to chmod your file permissions depending on your installation.


Running Rserve in OS X
1. Open a terminal instance. Type
R CMD Rserve



7. References

1. Gottardo R, Raftery AE, Yeung KY, Bumgarner RE: Robust estimation of cDNA microarray intensities with replicates. Journal of the American Statistical Association 2006, 101(473):30-40.

2. Gottardo R, Raftery AE, Yeung KY, Bumgarner RE: Bayesian Robust Inference for Differential Gene Expression in cDNA Microarrays with Multiple Samples. To appear in Biometrics 2006.