Hi, I have samples that are stained with a cytoplasmic neuronal marker (NeuN), a cytoplasmic glial marker (S100b) and which contain subcellular signals in several other channels (RNAscope staining). Here’s an example with NeuN + subcellular signals:
I’d like to segment the neurons and glia based on their cytoplasmic staining and then run subcellular detections on cell body (not nuclear) outlines. All of this would be done after running automated tissue detection. So the hierarchy would be: Tissue annotation > two different parent object classes (neuron and glia outlines) > several child classes (RNAscope signals) for each of those.
I am wondering what the best way of doing this would be in QuPath? Multiplexed classification (as described here: https://qupath.readthedocs.io/en/latest/docs/tutorials/multiplex_analysis.html) probably won’t work, since it relies on nucleus/cell detection first, before assigning them to classes. I guess a possible option would be to run neuron vs glia cell detection + corresponding subcellular detections in two separate steps, export measurements separately and then combine the data afterwards…. But I’m sure there’s a better way that I’m missing as a QuPath novice (e.g. detect neurons first, preserve annotations, Preserving rounds of cell detection?, detect glia, then run subcell. detections).