The complicated, evolving landscape of cancer mutations poses a formidable challenge to identify cancer genes among the large lists of mutations typically generated in NGS experiments. The ability to prioritize these variants is therefore of paramount importance. To address this issue we developed OncoScore, a text-mining tool that ranks genes according to their association with cancer, based on available biomedical literature. Receiver operating characteristic curve and the area under the curve (AUC) metrics on manually curated datasets confirmed the excellent discriminating capability of OncoScore (OncoScore cut-off threshold = 21.09; AUC = 90.3%, 95% CI: 88.1-92.5%), indicating that OncoScore provides useful results in cases where an efficient prioritization of cancer-associated genes is needed.
@article{arxiv.1703.05692,
title = {OncoScore: a novel, Internet-based tool to assess the oncogenic potential of genes},
author = {Rocco Piazza and Daniele Ramazzotti and Roberta Spinelli and Alessandra Pirola and Luca De Sano and Pierangelo Ferrari and Vera Magistroni and Nicoletta Cordani and Nitesh Sharma and Carlo Gambacorti-Passerini},
journal= {arXiv preprint arXiv:1703.05692},
year = {2017}
}