Somatic evolution plays a key role in development, cell differentiation, and normal aging, but also in diseases such as cancer. Understanding mechanisms of somatic mutability and how they can vary between cell lineages will likely play a crucial role in biological discovery and medical applications. This need has led to a proliferation of new technologies for profiling single-cell variation, each with distinctive capabilities and limitations that can be leveraged alone or in combination with other technologies. The enormous space of options for assaying somatic variation, however, presents unsolved informatics problems with regard to selecting optimal combinations of technologies for designing appropriate studies for any particular scientific questions. Versatile simulation tools are needed to explore and optimize potential study designs if researchers are to deploy multiomic technologies most effectively. In this study, we present a simulator allowing for the generation of synthetic data from a wide range of clonal lineages, variant classes, and sequencing technology choices, intended to provide a platform for effective study design in somatic lineage analysis. Users can input various properties of the somatic evolutionary system, mutation classes, and biotechnology options, and then generate samples of synthetic sequence reads and their corresponding ground truth parameters for a given study design. We demonstrate the utility of the simulator for testing and optimizing study designs for various experimental queries.

中文翻译：

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用于规划体细胞进化研究的克隆进化模拟器。

体细胞进化在发育、细胞分化和正常衰老以及癌症等疾病中发挥着关键作用。了解体细胞突变的机制以及它们如何在细胞谱系之间变化可能会在生物发现和医学应用中发挥至关重要的作用。这种需求导致了用于分析单细胞变异的新技术的激增，每种技术都具有独特的功能和局限性，可以单独使用或与其他技术结合使用。然而，分析体细胞变异的巨大选择空间提出了未解决的信息学问题，即选择最佳的技术组合来为任何特定的科学问题设计适当的研究。如果研究人员要最有效地部署多组学技术，就需要多功能模拟工具来探索和优化潜在的研究设计。在这项研究中，我们提出了一个模拟器，允许从各种克隆谱系、变异类别和测序技术选择中生成合成数据，旨在为体细胞谱系分析中的有效研究设计提供一个平台。用户可以输入体细胞进化系统、突变类别和生物技术选项的各种属性，然后为给定的研究设计生成合成序列读数的样本及其相应的地面实况参数。我们演示了模拟器在测试和优化各种实验查询的研究设计方面的实用性。