HotNet pathway analysis of mutation and copy number data
Overview
Introduction

HotNet is an algrithom for finding altered subnetworks in a large protein-protein interaction network conatinning a significant number of mutations and copy number alterations (CNAs).

Summary

There were 3 significant subnetworks identified in HotNet analysis.

Results
Significant subnetworks

HotNet identifies 3 altered subnetworks based on the matched somatic mutation and copy number alterations data. Table 1 showes the top 10 significant subnetworks.

Table 1.  Get Full Table Top 10 out of 3 subnetworks in ranked by p value. The last column of RepeatTimes shows how many times the subnetwork was picked up in differenct delta values.

Network No.ofgenes p-value RepeatTimes
LAMB1(14),PDE4DIP(10),RINT1(15),GFI1B(10) 4 0.0135 1
NRCAM(15),MET(14),PTPRB(6),TNC(11) 4 0.0135 1
NEFM(53),TNFRSF10C(54),TNFRSF10A(54),PON1(15),SCARB1(7) 5 0.0160 1
Methods & Data
Input

Somatic mutation data from Mutsig pipeline, copy number alterations derived from GISTIC pipeline and influence matrix derived from Human Protein Reference Database (HPRD) provided by HotNet website [1].

HotNet Method

HotNet is an algorithm for de novo identification of significantly altered subnetworks.First, it formulates an influence measure between pairs of genes in the network using a diffusion process defined on the graph. Second, it identifies subnetworks using either a combinatorial model or an enhanced influence model. Finally, it derives a two-stage multiple hypothesis test that mitigates the testing of a large number of hypotheses in subnetwork discovery [2].

References
[1] HotNet
[2] F. Vandin, E. Upfal, and B.J. Raphael., Algorithms for Detecting Significantly Mutated Pathways in Cancer, Journal of Computational Biology 18(3):507-22 (2011)