Mass cytometry (CyTOF) is a technology that has revolutionised single cell biology. One illuminating application of CyTOF has been in understanding the mechanisms of blood cancer resistance to therapy. Longitudinal studies of clinical cohorts during drug treatment provide a deeper understanding of the molecular changes that underlie sensitivity or resistance to treatment in each patient. However, understanding the biological impact of a cancer drug in such studies necessitates the integration of multiple CyTOF batches. To date, the integration of CyTOF datasets remains a challenge due to technical differences arising in multiple batches. To overcome this limitation, we developed an approach called CytofRUV for analysing multiple CyTOF batches which includes an R-Shiny application with diagnostics plots. CytofRUV can correct for batch effects and integrates data from a large number of patients and conditions across batches, to confidently compare cellular changes and correlate these with clinically relevant outcomes.

中文翻译：

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CytofRUV：删除不必要的变异以集成多个CyTOF数据集

质谱分析（CyTOF）是一项革新了单细胞生物学的技术。CyTOF的一个启发性应用是了解血液癌对治疗的抗性机制。药物治疗期间临床队列的纵向研究提供了对分子变化的更深入了解，这些分子变化是每个患者对治疗的敏感性或耐药性的基础。但是，在此类研究中了解癌症药物的生物学影响后，需要整合多个CyTOF批次。迄今为止，由于在多个批次中出现技术差异，CyTOF数据集的集成仍然是一个挑战。为了克服这一限制，我们开发了一种名为CytofRUV的方法来分析多个CyTOF批次，其中包括带有诊断图的R-Shiny应用程序。