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. Availability. Freely available at http://www.bioconductor.org/ under GPL license; project hosted at http://bimib.disco.unimib.it/ and https://github.com/BIMIB-DISCo/TRONCO.

Antoniotti, M., Caravagna, G., De Sano, L., Graudenzi, A., Mauri, G., Mishra, B., et al. (2016). Design of the TRONCO bioconductor package for TRanslational ONCOlogy. THE R JOURNAL, 8(2), 39-59 [10.32614/RJ-2016-032].

Design of the TRONCO bioconductor package for TRanslational ONCOlogy

ANTONIOTTI, MARCO
Primo
;
GRAUDENZI, ALEX;MAURI, GIANCARLO;Ramazzotti, D.
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. Availability. Freely available at http://www.bioconductor.org/ under GPL license; project hosted at http://bimib.disco.unimib.it/ and https://github.com/BIMIB-DISCo/TRONCO.
Articolo in rivista - Articolo scientifico
Statistics; Cancer Research; Computer Science
English
2016
8
2
39
59
open
Antoniotti, M., Caravagna, G., De Sano, L., Graudenzi, A., Mauri, G., Mishra, B., et al. (2016). Design of the TRONCO bioconductor package for TRanslational ONCOlogy. THE R JOURNAL, 8(2), 39-59 [10.32614/RJ-2016-032].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/132674
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