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Spatial transcriptomics #52
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Instead, ask the user how much they want to dilate each nuclear segmentation in the units of the image (e.g. um, can get from nucImgCalibration). Then, convert this dilation factor from physical units (e.g. um) to pixel units. See example under https://github.com/VPNL/FijiUpdateSite/blob/master/FijiPyPlugins/src/main/resources/scripts/Plugins/Organize_Fields_of_View/Separate_Image_Into_Fields_.py lines 113-147.
psgROIs = nucROIs | ||
nucROIs = [roienlarger.enlarge(nucROI,unitIncrease) for nucROI in psgROIs] | ||
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# Remove resulting overlap between newly expanded ROI |
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For lines 365+, needs to be under if statement at 361
# Merge the others | ||
other = ROITools.combineROIs(others) | ||
# Get the intersection of ROIs using the intersecting function | ||
AND = ROITools.getIntersectingROI([nucROI, other]) |
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Rename AND to intersection
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OUTPUT Fiji ROI storing the cropped region of interest | ||
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AR Jan 2022 | ||
AP Jun 2022 |
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Add description of change
Updated changes requested from AR pull request review |
Added the series of changes discussed with AR and AP 5/20/2022. Changes include new libraries imported and allowing the user to input an ROI dilation in order to analyze spatial transcriptomic data. The program iterates through the nuclear segmentations generated by the user earlier in the script, expands by the given expansion factor, and removes the overlaps. Missed an off by one error and added to this merge.