Alex M. Fichtenholtz, Nicholas D. Camarda, Eric K. Neumann
Technology Innovation, Foundation Medicine Inc.
Email: afichtenholtz@foundationmedicine.com, ndc9@duke.edu, eneumann@foundationmedicine.com
Pacific Symposium on Biocomputing 21:297-308(2016)
© 2016 World Scientific
Open Access chapter published by World Scientific Publishing Company and distributed under the terms of the Creative Commons Attribution (CC BY) 4.0 License.
Glial tumors have been heavily studied and sequenced, leading to scores of findings about altered genes. This explosion in knowledge has not been matched with clinical success, but efforts to understand the synergies between drivers of glial tumors may alleviate the situation. We present a novel molecular classification system that captures the combinatorial nature of relationships between alterations in these diseases. We use this classification to mine for enrichment of variants of unknown significance, and demonstrate a method for segregating unknown variants with functional importance from passengers and SNPs.