Fig. 3: Image data analysis allows the identification and quantification of ILCs and other relevant cell populations. | Nature Communications

Fig. 3: Image data analysis allows the identification and quantification of ILCs and other relevant cell populations.

From: Multiplexed histology analyses for the phenotypic and spatial characterization of human innate lymphoid cells

Fig. 3

a Fluorescence images and Probability Maps generated in Ilastik are loaded into CellProfiler. The dashed square represents the ROI. b Simplified analysis pipeline shows major steps in the data processing. Based on the nuclei probability map (ROI, upper left panel, red), nuclei are segmented as primary objects (upper middle panel: nuclear outlines within the ROI in red; upper left panel: nuclear outlines for the complete image in white). Mean fluorescence intensity (MFI) of nuclear stainings is measured within each nucleus. Using the segmented nuclei as seeding points and together with the membrane probability map (ROI, middle left panel, green), cells are segmented and identified as secondary objects (middle central panel: cell outlines within the ROI in green; middle left panel: cell outlines for the complete image in white). MFIs of membrane stainings are measured in each cell. The display of MFI values per object allows manual thresholding for each marker to classify cells into negative and positive subpopulations. ILCs are identified as LinCD3CD45+CD127+ cells, where Lin includes CD19, CD20, CD14, CD123, CD141, and FcεRIα. Lower middle panel: outline of 1 ILC in the ROI. Lower left panel: outlines of all ILCs in the complete image. c Dot plot depicts absolute numbers of relevant immune populations in all tissue areas analyzed. Data are shown as mean ± SD. ac (n = 5). Source data are provided as a Source data file.

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