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| Item Type: | Article | ||||
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| Title: | SMITH: spatially constrained stochastic model for simulation of intra-tumour heterogeneity | ||||
| Creators Name: | Streck, A. and 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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