儿童癌症是1至14岁儿童死因的第二大原因。虽然过去40年间生存率显著提高，但癌症的耐药性和复发仍然是重大挑战。单细胞技术的进展使得肿瘤可实现前所未有的分解，从而有助于揭示儿童癌症的异质性，识别易产生治疗耐药的细胞亚型。来自不同模式的单个细胞数据的快速积累需要开发新的计算方法来处理、可视化和分析单个细胞数据。我们在这里回顾了在儿童癌症背景下所采用或正在开发的单细胞方法。我们回顾了分析单细胞数据的计算方法，并讨论它们的应用最佳实践。最后，我们回顾了用这些方法分析的几个儿童肿瘤研究的影响和将单细胞研究纳入儿科肿瘤转化研究的未来方向。 © 2023年。作者（们）在Springer-Verlag GmbH Germany 独有许可之下，这是Springer Nature的一个部分。

Childhood cancer is the second leading cause of death in children aged 1 to 14. Although survival rates have vastly improved over the past 40 years, cancer resistance and relapse remain a significant challenge. Advances in single-cell technologies enable dissection of tumors to unprecedented resolution. This facilitates unraveling the heterogeneity of childhood cancers to identify cell subtypes that are prone to treatment resistance. The rapid accumulation of single-cell data from different modalities necessitates the development of novel computational approaches for processing, visualizing, and analyzing single-cell data. Here, we review single-cell approaches utilized or under development in the context of childhood cancers. We review computational methods for analyzing single-cell data and discuss best practices for their application. Finally, we review the impact of several studies of childhood tumors analyzed with these approaches and future directions to implement single-cell studies into translational cancer research in pediatric oncology.© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.