Motivation: We introduce TRanslational ONCOlogy (TRONCO), an open-source R package that implements the state-of-the-art algorithms for the inference of cancer progression models from (epi)genomic mutational profiles. TRONCO can be used to extract population-level models describing the trends of accumulation of alterations in a cohort of cross-sectional samples, e.g. retrieved from publicly available databases, and individual-level models that reveal the clonal evolutionary history in single cancer patients, when multiple samples, e.g. multiple biopsies or single-cell sequencing data, are available. The resulting models can provide key hints for uncovering the evolutionary trajectories of cancer, especially for precision medicine or personalized therapy.

De Sano, L., Caravagna, G., Ramazzotti, D., Graudenzi, A., Mauri, G., Mishra, B., et al. (2016). TRONCO: An R package for the inference of cancer progression models from heterogeneous genomic data. BIOINFORMATICS, 32(12), 1911-1913 [10.1093/bioinformatics/btw035].

TRONCO: An R package for the inference of cancer progression models from heterogeneous genomic data

CARAVAGNA, GIULIO
Secondo
;
RAMAZZOTTI, DANIELE;GRAUDENZI, ALEX;MAURI, GIANCARLO;ANTONIOTTI, MARCO
Ultimo
2016

Abstract

Motivation: We introduce TRanslational ONCOlogy (TRONCO), an open-source R package that implements the state-of-the-art algorithms for the inference of cancer progression models from (epi)genomic mutational profiles. TRONCO can be used to extract population-level models describing the trends of accumulation of alterations in a cohort of cross-sectional samples, e.g. retrieved from publicly available databases, and individual-level models that reveal the clonal evolutionary history in single cancer patients, when multiple samples, e.g. multiple biopsies or single-cell sequencing data, are available. The resulting models can provide key hints for uncovering the evolutionary trajectories of cancer, especially for precision medicine or personalized therapy.
Articolo in rivista - Articolo scientifico
Cancer; Bioinformatics; Machine Learning
English
1911
1913
3
De Sano, L., Caravagna, G., Ramazzotti, D., Graudenzi, A., Mauri, G., Mishra, B., et al. (2016). TRONCO: An R package for the inference of cancer progression models from heterogeneous genomic data. BIOINFORMATICS, 32(12), 1911-1913 [10.1093/bioinformatics/btw035].
De Sano, L; Caravagna, G; Ramazzotti, D; Graudenzi, A; Mauri, G; Mishra, B; Antoniotti, M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/100189
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