HyperModules App
Description
Hypermodules is a local graph search algorithm designed by Juri Reimand and Gary Bader. It was implemented in a command line version and as an app for Cytoscape 3.0 as part of Google Summer of Code 2013. Given a gene/protein interaction network, a set of mutation data with associated patients, and a set of clinical patient data, the algorithm aims to find modules within the interaction network most correlated with a clinical outcome. In particular, survival times are analyzed using the log rank test for survival curve comparison, and fisher's exact test is used for discrete clinical variables. Only pSNV's are considered, and the algorithm can be applied to many clinical variables. For more info, please consult the original paper; the algorithm is described in the second half.
Command-Line Version
The lightweight version is implemented in Java and compiled as an executable jar. To run, please ensure you have the latest version of Java installed on your machine. Then, navigate to the folder containing the jar file and run with the following command:
java -jar [nameofjar.jar] [PATH_TO_NETWORK] [PATH_TO_MUTATION_DATA] [PATH_TO_CLINICAL_DATA] [SHUFFLE_NUMBER] [STATISTICAL_TEST]
The shuffle number parameter should be between 100 and 5000, and the statistical test parameter is either "logrank" for survival data or "fisher" for data for a clinical variable. For example, using the attached example input files, assuming we have survival data and we want to do random shuffling of mutation associations 1000 times for accurate FDR discovery rate p-values, we run something that looks like this:
java -jar HyperModulesCommandLine-0.0.1-SNAPSHOT-jar-with-dependencies.jar /Users/user/HyperModules/allinteractions.csv /Users/user/HyperModules/mutation_data.csv /Users/user/HyperModules/clinical_data.csv 1000 logrank.
After the algorithm has finished running (NOTE: THIS MAY TAKE A LONG TIME, DEPENDING ON THE DENSITY OF THE TOPOLOGY OF THE INTERACTION NETWORK AND THE SIZE OF THE MUTATION DATA.), there are only three basic options: enter 0 to export the results to a specified filepath, after providing the p-value cutoff you want to consider (to save all data, use a p-value cutoff of 1), enter 1 to print the results to screen (again, after entering a p-value cutoff), or enter 2 to exit the running program (all results data will be lost).
*Download here:
Please consult the following example files as a reference for the accepted format of the input files:
* Protein-Protein Interactions: * Mutation Data: * Patient Survival Data: * Patient Fisher Variable Data:
Cytoscape App Version