美国宾夕法尼亚大学Nancy R. Zhang等研究人员合作，使用CellANOVA恢复单细胞批次整合中丧失的生物学信号。该项研究成果于2024年11月26日在线发表在《自然—生物技术》杂志上。

研究人员展示了当前单细胞数据整合的范式会去除具有生物学意义的变异，并引入失真。研究人员提出了一个统计模型和计算可扩展的算法——CellANOVA（单细胞状态空间方差分析），该方法利用实验设计显式恢复在单细胞数据整合过程中丧失的生物学信号。

CellANOVA使用“对照池”设计概念，适用于多种设置，能够将不需要的变异与感兴趣的生物学变异分开，并恢复微妙的生物学信号。研究人员将CellANOVA应用于多种情境，并通过正交实验验证恢复的生物学信号。

特别地，研究人员展示了CellANOVA在单细胞和单核数据整合的挑战性案例中是有效的，它恢复了微妙的生物学信号，这些信号可以通过外部数据验证和复制。

据悉，数据整合用于对齐不同批次的细胞，已成为单细胞数据分析的基石，直接影响下游结果。目前，对于何时可以将样本之间的生物学差异与批次效应区分开来，尚无明确的指导原则。

附：英文原文

Title: Recovery of biological signals lost in single-cell batch integration with CellANOVA

Author: Zhang, Zhaojun, Mathew, Divij, Lim, Tristan L., Mason, Kaishu, Martinez, Clara Morral, Huang, Sijia, Wherry, E. John, Susztak, Katalin, Minn, Andy J., Ma, Zongming, Zhang, Nancy R.

Issue&Volume: 2024-11-26

Abstract: Data integration to align cells across batches has become a cornerstone of single-cell data analysis, critically affecting downstream results. Currently, there are no guidelines for when the biological differences between samples are separable from batch effects. Here we show that current paradigms for single-cell data integration remove biologically meaningful variation and introduce distortion. We present a statistical model and computationally scalable algorithm, CellANOVA (cell state space analysis of variance), that harnesses experimental design to explicitly recover biological signals that are erased during single-cell data integration. CellANOVA uses a ‘pool-of-controls’ design concept, applicable across diverse settings, to separate unwanted variation from biological variation of interest and allow the recovery of subtle biological signals. We apply CellANOVA to diverse contexts and validate the recovered biological signals by orthogonal assays. In particular, we show that CellANOVA is effective in the challenging case of single-cell and single-nucleus data integration, where it recovers subtle biological signals that can be validated and replicated by external data.

DOI: 10.1038/s41587-024-02463-1

Source: https://www.nature.com/articles/s41587-024-02463-1