癌症演化模拟对于研究细胞健康度中选择和突变速率的影响非常有用。然而，大多数方法基于晶格且无法模拟真实大小的肿瘤，或者忽略空间约束且缺乏真实肿瘤的克隆动力学。SMITH是一种高效且可解释的癌症演化模型，结合了分支过程和新的约束机制，该机制基于个体克隆大小和整个肿瘤种群的大小限制克隆生长。我们证明了约束足以在肿瘤类型、空间模型和癌症样本中诱导丰富的克隆动态，并允许在桌面PC上在短时间内模拟十亿个细胞的清晰几何解释和模拟。SMITH是C#实现的，可在https://bitbucket.org/schwarzlab/smith免费使用。我们提供了配套的Python包PyFish进行可视化，可在https://bitbucket.org/schwarzlab/pyfish获取。补充数据可在Bioinformatics在线获得。 ©作者（2023）。由牛津大学出版社出版。

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.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.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.Supplementary data are available at Bioinformatics online.© The Author(s) 2023. Published by Oxford University Press.