Learning mutational graphs of individual tumour evolution from single-cell and multi-region sequencing data

1 code implementation • 4 Sep 2017 • Daniele Ramazzotti, Alex Graudenzi, Luca De Sano, Marco Antoniotti, Giulio Caravagna

Compared to other tools, TRaIT supports multi-region and single-cell sequencing data within the same statistical framework, and delivers expressive models that capture many complex evolutionary phenomena.

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

2 code implementations • 8 May 2017 • Lucrezia Patruno, Edoardo Galimberti, Daniele Ramazzotti, Giulio Caravagna, Luca De Sano, Marco Antoniotti, Alex Graudenzi

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.

SIMLR: A Tool for Large-Scale Genomic Analyses by Multi-Kernel Learning

1 code implementation • 21 Mar 2017 • Bo Wang, Daniele Ramazzotti, Luca De Sano, Junjie Zhu, Emma Pierson, Serafim Batzoglou

We here present SIMLR (Single-cell Interpretation via Multi-kernel LeaRning), an open-source tool that implements a novel framework to learn a sample-to-sample similarity measure from expression data observed for heterogenous samples.

Clustering Dimensionality Reduction