Although the role of evolutionary process in cancer progression is widely accepted, increasing attention is being given to the evolutionary mechanisms that can lead to differences in clinical outcome. Recent studies suggest that the temporal order in which somatic mutations accumulate during cancer progression is important. Single-cell sequencing provides a unique opportunity to examine the mutation order during cancer progression. However, the errors associated with single-cell sequencing complicate this task. We propose a new method for inferring the order in which somatic mutations arise within a tumor using noisy single-cell sequencing data that incorporates the errors that arise from the data collection process. Using simulation, we show that our method outperforms existing methods for identifying mutation order in most cases, especially when the number of cells is large. Our method also provides a means to quantify the uncertainty in the inferred mutation order along a fixed phylogeny. We apply our method to empirical data from colorectal and prostate cancer patients.

中文翻译：

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一种推断癌症进展过程中发生突变顺序的系统发育方法

尽管进化过程​​在癌症进展中的作用已被广泛接受，但越来越多的关注可能导致临床结果差异的进化机制。最近的研究表明，癌症进展过程中体细胞突变积累的时间顺序很重要。单细胞测序提供了一个独特的机会来检查癌症进展过程中的突变顺序。然而，与单细胞测序相关的错误使这项任务复杂化。我们提出了一种新方法，可以使用包含数据收集过程中出现的错误的嘈杂单细胞测序数据来推断肿瘤内发生体细胞突变的顺序。使用模拟，我们表明我们的方法在大多数情况下优于现有的识别突变顺序的方法，尤其是当单元格数量很大时。我们的方法还提供了一种量化沿固定系统发育推断的突变顺序的不确定性的方法。我们将我们的方法应用于结肠直肠癌和前列腺癌患者的经验数据。