WMAXC Weighted MAXimum Clique method for identifying condition specific sub-network


2013/11/15: Source codes and data sets are updated.
WMAXC reveals a subset of genes which are closely related to a particular disease. It integrates gene expression data and protein-protein interaction information to construct molecular network, and then extracts the most density connected sub-network using an integration of a global search method and efficient projection procedure.
Paper Amgalan, B. and Lee, H. (2013) Weighted MAXimum Clique method for identifying condition specific sub-network.
Source codes
Source codes were implemented in MatLab and are available here. Instructions for running source codes are here. The source codes require four input files such as Cancer and Normal samples in matrix forms, PPI network as a list of interactions and a list of well known cancer related genes. The gene list is used to test performance of the method. Input files for ovarian cancer data can be downloaded from here and for prostate cancer data can be downloaded from here. Source codes and input files should be located in same folder.
Data sets

The ovarian cancer data sets used in the experiments were collected from TCGA(2011), and the prostate cancer data sets can be found from GEO(Lapointe et al., 2004). Protein-protein interaction data sets were collected from the Human Protein Reference Database HPRD(Prasad et al.,2009) consisting of a list of interactions in the PPI network.

bayaraa at gist.ac.kr, hyunjulee at gist.ac.kr