Please note that software on this page is provided for historical continuity but it is no longer actively maintained. This code has been superseded by R/maanova.
MAANOVA is a set of functions written in Matlab for the analysis of variance on microarray data. These functions are well tested in Matlab R13 for Windows(98/NT4/2000) and Linux Redhat 7.0-8.0. We cannot guarantee that software downloaded from this page will be functional with current releases of Matlab. You may encounter problems in other operating systems or other Matlab versions. Please contact Keith Sheppard for further information about the programs.
Warranty Disclaimer and Copyright Notice
The Jackson Laboratory makes no representation about the suitability or accuracy of this software for any purpose, and makes no warranties, either express or implied, including merchantability and fitness for a particular purpose or that the use of this software will not infringe any third party patents, copyrights, trademarks, or other rights. The software are provided "as is".
This software is provided to enhance knowledge and encourage progress in the scientific community. This is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
Download the programs
Download the Windows version or the Linux version of the software. The only difference between the Windows and Linux version is the cmex function (currently there is only one, clowess). If you encounter problems using that function, type "mex -O clowess.c" to recompile it.
Download the data files and demo scripts
The following data were analyzed using MAANOVA 2.0 software. Download and run the demo scripts to get a better understanding of the function syntax and the statistical ideas behind it.
Note that if you put the script in a different directory than MAANOVA
codes, you need to add the path of MAANOVA to the workspace. Type
'help addpath' in Matlab for detail.
- TIGR double loop and double reference example: A 20-array experiment
- Crawford fish experiment: A big loop experiment
- Paigen's 300-gene example: A multiple factor 28-array experiment
Using the programs
Analysis of variance for gene expression microarray data
Kerr MK, Martin M, Churchill GA.
J Comput Biol. 2000;7(6):819-37.