Fig. 2: Computational outline of ARTseq-FISH.

a A condensed summary of the automated computational pipeline that converts the raw microscope images into a single-cell dataset, providing the abundance of each target per cell. First, the hybridisation signal is detected, followed by an iterative AI-based segmentation approach, the segments are clustered, and the cells are reconstructed in 3D. Next, an image drift correction is applied to align the hybridisation between rounds. In the final step, these hybridisation signals are decoded and assigned to the targets as well as individual cells. b Reconstructed images show all the detected molecules in the cells cultured on micropattern 48 h after leukaemia inhibitory factor (LIF) withdrawal. The spots are subdivided into three classes: mRNA (yellow), protein (blue) and phosphorylated protein (brown). Scale bar, 20 µm.