Cells function within the context of tissue architecture and continuously interact with their local environment. The transcriptome of a cell varies in accordance with the location and the environment. Cells express genes related to cell communication and genes involved in downstream pathways. Interaction with the neighboring cells influences the transcriptome of a cell. Spatial transcriptomics (ST), by measuring the transcriptome of cells as well as their locations, can contribute to our understanding of how tissue architecture and cell-cell interaction influence the transcriptome.
We apply image processing and machine-learning algorithms to single-cell and spatial genomics data to understand gene regulatory rules involved in cell-cell interactions.