HIT’nDRIVE: Multi-driver Gene Prioritization Based on Hitting Time
- Cite this paper as:
- Shrestha R. et al. (2014) HIT’nDRIVE: Multi-driver Gene Prioritization Based on Hitting Time. In: Sharan R. (eds) Research in Computational Molecular Biology. RECOMB 2014. Lecture Notes in Computer Science, vol 8394. Springer, Cham
A key challenge in cancer genomics is the identification and prioritization of genomic aberrations that potentially act as drivers of cancer. In this paper we introduce HIT’nDRIVE, a combinatorial method to identify aberrant genes that can collectively influence possibly distant “outlier” genes based on what we call the “random-walk facility location” (RWFL) problem on an interaction network. RWFL differs from the standard facility location problem by its use of “multi-hitting time”, the expected minimum number of hops in a random walk originating from any aberrant gene to reach an outlier. HIT’nDRIVE thus aims to find the smallest set of aberrant genes from which one can reach outliers within a desired multi-hitting time. For that it estimates multi-hitting time based on the independent hitting times from the drivers to any given outlier and reduces the RWFL to a weighted multi-set cover problem, which it solves as an integer linear program (ILP). We apply HIT’nDRIVE to identify aberrant genes that potentially act as drivers in a cancer data set and make phenotype predictions using only the potential drivers - more accurately than alternative approaches.
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