Outputs from many experiment platforms are commonly lists of genes. Exploring the relevance among these genes in the list(s) is very useful to understand the perturbed pathways and functions in the studied disease and phenotype.

To address this question in a network approach, we present a package called GenRev. GenRev is a Python software package that identifies subnetworks for a set of genes from a large network. Three algorithms are implemented in GenRev, the Klein-Ravi algorithm for node weighted Steiner tree problem, the limited k-walk algorithm and a heuristic local search algorithm. Each algorithm is implemented in an independent module. Another analysis module is also developed for graph clustering and gene ranking. This package can be used either as a standalone application, or as Python modules. The left figure shows the flowchart of GenRev.