I usually keep the class column as the first column in the data sheet. The CSV should include at least XY Coordinates and a Class column. To start with, load in your CSV file as before, through the File menu in the main CytoMAP interface. Using tSNE or other dimensionality reduction to isolate clusters of cells, manually gate those, and use those clusters for your neighborhood analysis.Taking classes defined in QuPath to form the regions.I have not worked on getting the actual masks of the regions back into QuPath.įor reference, the source image is in the upper left (same as for the previous guide) showing Cytokeratin/tumor areas in teal, and assorted immune markers which show up more frequently on the top-left part of the image.Īs always, the official documentation can be found here - Guide is only accurate as of 1.4.13: There will be two versions of the guide below: Using the same sort of scripts as last time, you can also get the regions that you define back into QuPath, at least in terms of which cells are in which regions. It ends up finding solid tumor, tumor borders, inflamed stroma, and normal stroma. In some of the images below, I ask CytoMAP to divide a field of view including dense cytokeratin annotations into four regions. Region/neighborhood analysis allows you to cluster groups of cells into “environments” and look at what types of cells are interacting most frequently, and how those areas connect with one another. Groups of cells form environments, whether that is organ/tissue related, tumor related, or sometimes borders between two tissue types. Well, sometimes just classifying cells is not enough to get a good grasp of what is going on in an image, especially when you have dozens of markers and many different phenotypes. The data shown will be largely based off of the CSV exports used in the last guide, so you can download (second post) as a test set if you are having problems getting things working. This rather quick guide is mostly focused on using the neighborhood analysis tools in CytoMAP to analyze multiplex data, though they could be used for pretty much any CSV that includes XY (and possibly Z) coordinates. Hi again, everyone interested in cluster analysis and tissue neighborhoods!
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