Supplementary Information

The first two files are the 128 and 144 gene groups with information gathered from the Network of Cancer Genes (NCG 3.0) 1 ). You can download the 128 information here and the 144 information here.

The second two files are the 128 and 144 gene groups with information gathered from PANTHER classication system relating to gene ontology and pathway information 2 ). You can download the 128 information here and the 144 information here.

Demo with Instructions

MBICluster.m is a MATLAB program that implements the Maximum Block Improvement algorithm.

Running the Demo

Requirement: MATLAB

  1. A copy of MATLAB and the statistics toolkit is needed to run this software.

  2. Download MATLAB and install it if needed.

Requirement: Demo files and test database.

  1. You need to download the demo code here.

  2. You will also need to download a copy of the test data set here. (Test data adapted from Shedden et. al 3 )

Next: Running the Demo on Linux/Windows (MATLAB GUI)

    Before running the MATLAB GUI you need to unpack code_demo.tar (using an untar application) and move the testdat.mat file into the unpacked directory. Then simply open that folder in the MATLAB GUI and type the following to run the demo: 
    code_demo

Next: Running the Demo on Linux (console)

  1. Unpack the Demo:
    2. tar xvf code_demo.tar
  2. Change to the code_demo directory:
    3. cd code_demo
  3. No configuration should be needed, but you will need to move the test data to the code_demo directory. If it was in the same directory as code_demo.tar you can run the following command:
    4. mv ../testdata.mat .
  4. Finally, you can run the demo with the following command:
    5. matlab -nodisplay -nosplash -r code_demo

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Footnotes

  1. Network of Cancer Genes 3.0 Source

  2. PANTHER classification system. Source

  3. Shedden, K. et al. Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study. Nat Med 14, 822–827 (2008). Source