Single-cell genomics has transformed our ability to examine cell fate choice. Examining cells along a computationally ordered ‘pseudotime’ offers the potential to unpick subtle changes in variability and covariation among key genes. We describe an approach, scHOT—single-cell higher-order testing—which provides a flexible and statistically robust framework for identifying changes in higher-order interactions among genes. scHOT can be applied for cells along a continuous trajectory or across space and accommodates various higher-order measurements including variability or correlation. We demonstrate the use of scHOT by studying coordinated changes in higher-order interactions during embryonic development of the mouse liver. Additionally, scHOT identifies subtle changes in gene–gene correlations across space using spatially resolved transcriptomics data from the mouse olfactory bulb. scHOT meaningfully adds to first-order differential expression testing and provides a framework for interrogating higher-order interactions using single-cell data.

单细胞基因组学已经改变了我们检查细胞命运选择的能力。检查沿计算有序的“伪时间”的细胞提供了揭开关键基因之间变异性和协变细微变化的潜力。我们描述了一种方法scHOT（单细胞高阶测试），它提供了一种灵活且统计上可靠的框架，用于识别基因之间的高阶交互作用中的变化。scHOT可应用于沿连续轨迹或跨空间的细胞，并适应各种高阶测量，包括可变性或相关性。我们通过研究小鼠肝脏胚胎发育过程中高阶相互作用的协同变化来证明scHOT的使用。另外，scHOT使用来自小鼠嗅球的空间分辨的转录组学数据，识别整个空间中基因与基因相关性的细微变化。scHOT有意义地增加了一阶差异表达测试，并提供了使用单细胞数据询问更高阶相互作用的框架。