Shi Hongyu, Zatzman Matthew, Shah Sohrab, McPherson Andrew
Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Methods Mol Biol. 2025;2932:137-152. doi: 10.1007/978-1-0716-4566-6_7.
Somatic copy number changes modify gene expression and drive cancer development and progression. Single-cell techniques now allow for the profiling of both gene expression and copy number, opening the possibility of linking expression changes with copy number changes at a single-cell level. However, joint measurement of both expression and copy number from the same cell is not commonplace, and thus joint analysis of expression and copy number requires computational integration of the two modalities. TreeAlign is a method for matching cells in single-cell RNA (scRNA) data to clones inferred from single-cell whole genome sequence (scWGS) data. TreeAlign is phylogeny aware and capable of robustly modeling the effect of gene dosage on gene expression. In this chapter, we provide a practical guide for using TreeAlign to jointly analyze copy number and gene expression from single-cell whole genome sequencing and single-cell RNA sequencing datasets.
体细胞拷贝数变化会改变基因表达，并推动癌症的发生和发展。单细胞技术现在能够对基因表达和拷贝数进行分析，从而开启了在单细胞水平上关联表达变化与拷贝数变化的可能性。然而，从同一细胞中同时测量表达和拷贝数的情况并不常见，因此对表达和拷贝数的联合分析需要对这两种模式进行计算整合。TreeAlign是一种将单细胞RNA（scRNA）数据中的细胞与从单细胞全基因组序列（scWGS）数据推断出的克隆进行匹配的方法。TreeAlign具有系统发育意识，能够稳健地模拟基因剂量对基因表达的影响。在本章中，我们提供了一份实用指南，介绍如何使用TreeAlign对来自单细胞全基因组测序和单细胞RNA测序数据集的拷贝数和基因表达进行联合分析。
