Random Forest as a Tumour Genetic Marker Extractor
Genomics
2019-11-27 v1 Machine Learning
Abstract
Finding tumour genetic markers is essential to biomedicine due to their relevance for cancer detection and therapy development. In this paper, we explore a recently released dataset of chromosome rearrangements in 2,586 cancer patients, where different sorts of alterations have been detected. Using a Random Forest classifier, we evaluate the relevance of several features (some directly available in the original data, some engineered by us) related to chromosome rearrangements. This evaluation results in a set of potential tumour genetic markers, some of which are validated in the bibliography, while others are potentially novel.
Keywords
Cite
@article{arxiv.1911.11471,
title = {Random Forest as a Tumour Genetic Marker Extractor},
author = {Raquel Pérez-Arnal and Dario Garcia-Gasulla and David Torrents and Ferran Parés and Ulises Cortés and Jesús Labarta and Eduard Ayguadé},
journal= {arXiv preprint arXiv:1911.11471},
year = {2019}
}