肿瘤亚克隆重建模拟方法的评估
Evaluation of simulation methods for tumor subclonal reconstruction
AI总结：
本文评估了肿瘤亚克隆重建的现有模拟方法，分析了其优缺点并提出改进建议，为推动肿瘤基因组模拟领域的发展提供了重要参考。
摘要：
大多数肿瘤起源于单个细胞，其演化可通过以小体细胞突变（SSMs）、拷贝数变异（CNAs）、结构变异（SVs）和非整倍性等常见改变为特征的谱系进行遗传追踪。由于大多数肿瘤中这些改变的复杂性，以及测序方案和变异检测算法引入的错误，需要肿瘤亚克隆重建算法在计算机模拟中重现DNA序列组成和肿瘤演化。随着此类算法日益增多，迫切需要一致且全面的基准测试，这依赖于模拟工具生成的真实肿瘤测序数据。在此，我们评估了当前的模拟方法，指出了其优缺点，并提出了改进建议。本综述还探讨了该领域潜在的新研究方向。本工作旨在作为理解和增强肿瘤基因组模拟的资源，推动该领域的发展。
英文摘要：
Most neoplastic tumors originate from a single cell, and their evolution can be genetically traced through lineages characterized by common alterations such as small somatic mutations (SSMs), copy number alterations (CNAs), structural variants (SVs), and aneuploidies. Due to the complexity of these alterations in most tumors and the errors introduced by sequencing protocols and calling algorithms, tumor subclonal reconstruction algorithms are necessary to recapitulate the DNA sequence composition and tumor evolution in silico. With a growing number of these algorithms available, there is a pressing need for consistent and comprehensive benchmarking, which relies on realistic tumor sequencing generated by simulation tools. Here, we examine the current simulation methods, identifying their strengths and weaknesses, and provide recommendations for their improvement. Our review also explores potential new directions for research in this area. This work aims to serve as a resource for understanding and enhancing tumor genomic simulations, contributing to the advancement of the field.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
