DICER - Differential Correlation in Expression for meta-module RecoveryDICER is a tool for advanced analysis of differential co-expression (DC) case-control gene expression data.
Given two (or more) sets of expression profiles labeled generically by the classes 'case' and 'control', it seeks two types of groups of genes:
Examples of differential co-expression patterns that DICER looks for.
Java executable distribution
DICER code API
Download the source code from here
To work with the code, download this jar (from EXPANDER)
This distribution is our officially supported executable for DICER. This binary is completely self-contained and should work out of the box without any issues. The package includes a small test dataset.
The software is freely available under the GNU Lesser General Public License, version 3, or any later version at your choice.
DICER is a research tool, still in the development stage. Hence, it is not presented as error-free, accurate, complete, useful, suitable for any specific application or free from any infringement of any rights. The Software is licensed AS IS, entirely at the user's own risk.
java -jar dicer.jar <expression matrix> <classes file> <index of the class of interest><output files prefix><Optional: out=1 to print the graphs><Optional: K=value (default is 2)>
Detailed description of parameters here or in the API.
java -jar dicer.jar AD\top3000.txt AD\classesFile.txt 0 ad_results.txt
java -jar dicer.jar AD\top3000.txt AD\classesFile.txt 0 ad_results.txt out=1
java -jar dicer.jar AD\top3000.txt AD\classesFile.txt 0 ad_results.txt out=1 K=1
Dissection of regulatory networks that are altered in disease via differential co-expression, PLoS ComBio 2013
David Amar, Hershel Safer, Ron Shamir.