cancer_pathway Files

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Release of CovEx version 1.0
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This software is free, open source software released under the GNU General Public License.

CovEx is an algorithm for finding significantly altered exclusive functional modules in a large protein-protein interaction networks. The software expects as input cancer mutation data, and ouputs all significant modules and further the possible patient related driver modules. Briefly, it works in three steps: first, CovEx identifies high score modules based on Dendrix weight for each considered gene in a local network based on a deduced influence graph. Then, modules with significant coverage and exclusivity properties are selected. Finally, possible patient related driver modules are further identified.

CovEx also provides consensus algorithms to identify functional modules for results obtained based on different protein-protein interaction networks.

This software is free to use, modify, redistribute without any restrictions, except including the license provided with the distribution. 

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Release of UniCovEx version 1.0
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This software is free, open source software released under the GNU General Public License.

UniCovEx is an algorithm for systematic identification of uniformly mutually exclusive alterations by integrative analysis of cancer genomic data and large protein-protein interaction (PPI) networks. The software expects as input cancer mutation data, and ouputs a number of significant uniformly mutually exclusive gene sets and further patient specific driver gene sets. Briefly, it works in three steps: first, UniCovEx identifies candidate gene sets for the specified considered genes by an exclusivity greedy strategy in each local network of the influence network derived from a PPI network. The considered genes are all the mutated genes by default or a subset of mutated genes specified by the user. Then, we select the minimum number of large score gene sets such that each of the patients has mutaitons in the selected gene sets. Finally, a generalized minimum set cover model is applied to identify patient specific driver gene sets.

Compared to CovEx, another software developed in our lab, UniCovEx considers the uniform property of mutually exclusive alterations. The two algorithms identify cancer related gene sets by different ways. CovEx searches for candidate gene sets by a linear programming model. In constrast, UniCovEx searches for candidate gene sets by an exclusivity greedy strategy. In addition, UniCovEx generalizes the minimum set cover model to  identify patient specific driver gene sets. A number of gene sets can be predicted for a specific patient.

This software is free to use, modify, redistribute without any restrictions, except including the license provided with the distribution. 

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Release of ComCovEx version 1.0
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This software is free, open source software released under the GNU General Public License.

ComCovEx is an algorithm for systematic identification of the common driver modules between two cancer types by integrative analysis of cancer genomic data and large protein-protein interaction (PPI) networks. The software expects as input cancer mutation data, and outputs the predicted common driver gene modules for both cancer types. Briefly, it works in three steps. First, ComCovEx searches for the local network centered at each mutated gene in an influence network obtained by a random walk model based on a PPI network. Then ComCovEx identifies the candidate common driver modules in each local network by an exclusivity directed greedy strategy. Finally, ComCovEx outputs the predicted common driver modules with significantly large coverage and mutually exclusive scores for both cancer types.

This software is free to use, modify, redistribute without any restrictions, except including the license provided with the distribution.