Edinburgh Research Explorer

Design of the TRONCO BioConductor Package for TRanslational ONCOlogy

Research output: Contribution to journalArticle

  • Marco Antoniotti
  • Giulio Caravagna
  • Luca De Sano
  • Alex Graudenzi
  • Giancarlo Mauri
  • Bud Mishra
  • Daniele Ramazzotti

Related Edinburgh Organisations

Open Access permissions

Open

Original languageEnglish
Pages (from-to)39-59
Number of pages21
JournalThe R Journal
Volume8
Issue number2
Early online date21 Oct 2016
DOIs
Publication statusE-pub ahead of print - 21 Oct 2016

Abstract

Models of cancer progression provide insights on the order of accumulation of genetic alterations during cancer development. Algorithms to infer such models from the currently available mutational profiles collected from different cancer patients (cross-sectional data) have been defined in the literature since late the 90s. These algorithms differ in the way they extract a graphical model of the
events modelling the progression, e.g., somatic mutations or copy-number alterations.
TRONCO is an R package for TRanslational ONcology which provides a series of functions to assist the user in the analysis of cross-sectional genomic data and, in particular, it implements algorithms that aim to model cancer progression by means of the notion of selective advantage. These algorithms are proved to outperform the current state-of-the-art in the inference of cancer progression
models. TRONCO also provides functionalities to load input cross-sectional data, set up the execution of the algorithms, assess the statistical confidence in the results, and visualize the models.

Download statistics

No data available

ID: 31828110