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GitHub repository of the PMCE Framework. F. Angaroni, K. Chen, C. Damiani, G. Caravagna, A. Graudenzi, D. Ramazotti, PMCE: efficient inference of expressive models of cancer evolution with high prognostic power, Bioinformatics, 2021; btab717, https://doi.org/10.1093/bioinformatics/btab717

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PMCE: efficient inference of expressive models of cancer evolution with high prognostic power

In this repository we provide the code for the inference of Hidden Extended Suppes-Bayes Causal Networks (H-ESBCNs) in the directory named "HESBCN" and the scripts to replicate the PMCE analysis as presented in the paper (directory named "Utilities").

For the theoretical and methodological details, please refer to: Fabrizio Angaroni, Kevin Chen, Chiara Damiani, Giulio Caravagna, Alex Graudenzi, Daniele Ramazotti, PMCE: efficient inference of expressive models of cancer evolution with high prognostic power, Bioinformatics, 2021;, btab717, https://doi.org/10.1093/bioinformatics/btab717

Please feel free to contact us if you have problems running our tool at [email protected] and [email protected].

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GitHub repository of the PMCE Framework. F. Angaroni, K. Chen, C. Damiani, G. Caravagna, A. Graudenzi, D. Ramazotti, PMCE: efficient inference of expressive models of cancer evolution with high prognostic power, Bioinformatics, 2021; btab717, https://doi.org/10.1093/bioinformatics/btab717

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