cyTRON and cyTRON/JS: two Cytoscape-based applications for the inference of cancer evolution models

The increasing availability of sequencing data of cancer samples is fueling the development of algorithmic strategies to investigate tumor heterogeneity and infer reliable models of cancer evolution. We here build up on previous works on cancer progression inference from genomic alteration data, to deliver two distinct Cytoscape-based applications, which allow to produce, visualize and manipulate cancer evolution models, also by interacting with public genomic and proteomics databases. In particular, we here introduce cyTRON, a stand-alone Cytoscape app, and cyTRON/JS, a web application which employs the functionalities of Cytoscape/JS. cyTRON was developed in Java; the code is available at https://github.com/BIMIB-DISCo/cyTRON and on the Cytoscape App Store http://apps.cytoscape.org/apps/cytron. cyTRON/JS was developed in JavaScript and R; the source code of the tool is available at https://github.com/BIMIB-DISCo/cyTRON-js and the tool is accessible from https://bimib.disco.unimib.it/cytronjs/welcome.

[1]  Giulio Caravagna,et al.  Learning mutational graphs of individual tumour evolution from single-cell and multi-region sequencing data , 2017, BMC Bioinformatics.

[2]  Giulio Caravagna,et al.  Learning mutational graphs of individual tumor evolution from multi-sample sequencing data , 2017, bioRxiv.

[3]  N. McGranahan,et al.  The causes and consequences of genetic heterogeneity in cancer evolution , 2013, Nature.

[4]  P. Nowell The clonal evolution of tumor cell populations. , 1976, Science.

[5]  Daniele Ramazzotti,et al.  Modeling Cumulative Biological Phenomena with Suppes-Bayes Causal Networks , 2016, bioRxiv.

[6]  Giancarlo Mauri,et al.  TRONCO: an R package for the inference of cancer progression models from heterogeneous genomic data , 2015, bioRxiv.

[7]  Giancarlo Mauri,et al.  CAPRI: Efficient Inference of Cancer Progression Models from Cross-sectional Data , 2014, bioRxiv.

[8]  Giancarlo Mauri,et al.  Inferring Tree Causal Models of Cancer Progression with Probability Raising , 2013, bioRxiv.

[9]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[10]  K. Kinzler,et al.  Cancer genes and the pathways they control , 2004, Nature Medicine.

[11]  Giancarlo Mauri,et al.  Design of the TRONCO BioConductor Package for TRanslational ONCOlogy , 2015 .

[12]  Giancarlo Mauri,et al.  Algorithmic methods to infer the evolutionary trajectories in cancer progression , 2015, Proceedings of the National Academy of Sciences.

[13]  Zoltan Szallasi,et al.  Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal , 2018, Cell.