Combinatorial Detection of Conserved Alteration Patterns for Identifying Cancer Subnetworks
Abstract
Background
Advances in large scale tumor sequencing have lead to an understanding that there are combinations of genomic and transcriptomic alterations speciflc to tumor types, shared across many patients. Unfortunately, computational identiflcation of functionally meaningful shared alteration patterns, impacting gene/protein interaction subnetworks, has proven to be challenging.
Findings
We introduce a novel combinatorial method, cd-CAP, for simultaneous detection of connected subnetworks of an interaction network where genes exhibit conserved alteration patterns across tumor samples. Our method differentiates distinct alteration types associated with each gene (rather than relying on binary information of a gene being altered or not), and simultaneously detects multiple alteration proflle conserved subnetworks.
Conclusions
In a number of The Cancer Genome Atlas (TCGA) data sets, cd-CAP identifled large biologically signiflcant subnetworks with conserved alteration patterns, shared across many tumor samples.
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