Abstract
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 a novel 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 any higher order measurement including variability or correlation. We demonstrate the utility 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.
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