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SMITH: spatially constrained stochastic model for simulation of intra-tumour heterogeneity

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Item Type:Article
Title:SMITH: spatially constrained stochastic model for simulation of intra-tumour heterogeneity
Creators Name:Streck, A., Kaufmann, T.L. and Schwarz, R.F.
Abstract:MOTIVATION: Simulations of cancer evolution are highly useful to study the effects of selection and mutation rates on cellular fitness. However, most methods are either lattice-based and cannot simulate realistically-sized tumours, or they omit spatial constraints and lack the clonal dynamics of real-world tumours. RESULTS: SMITH is an efficient and explainable model of cancer evolution that combines a branching process with a new confinement mechanism limiting clonal growth based on the the size of the individual clones as well as the overall tumour population. We demonstrate how confinement is sufficient to induce the rich clonal dynamics observed in spatial models and cancer samples across tumour types, while allowing for a clear geometric interpretation and simulation of one billion cells within a few minutes on a desktop PC. AVAILABILITY AND IMPLEMENTATION: SMITH is implemented in C# and freely available at https://bitbucket.org/schwarzlab/smith. For visualisations we provide the accompanying Python package PyFish at https://bitbucket.org/schwarzlab/pyfish.
Keywords:Computer Simulation, Neoplasms, Software
Source:Bioinformatics
ISSN:1367-4803
Publisher:Oxford University Press
Volume:39
Number:3
Page Range:btad102
Date:March 2023
Official Publication:https://doi.org/10.1093/bioinformatics/btad102
PubMed:View item in PubMed

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