If you mean can you create a workflow where CellProfiler does some preprocessing, the result is then sent to ImageJ, and a number is pulled back into CellProfiler and processing continues, then no, not currently possible- the RunImageJMacro is designed to only pull back images from ImageJ, not numerical data, though that may change in our next release based on some work our team is doing now. I can not get numerical values back from imageJ into a running CP pipeline?.Typically you just have to right click or control click in the box to get the list of Metadata things to use. Nope, not true! Any piece of metadata extracted in the Metadata module can be used in file and/or names (in SaveCroppedObjects or other File export module). I can not use CP to export individual PrimaryObjects with a file name that corresponds to some metadata (e.g. Even if it is not a direct replacement, depending on the exact nature of your biological question and the exact measurement you are doing now, the measurements from CellProfiler MAY (or may not, without knowing your current measurement and your exact question I can’t say) end up being a better measure of your biology than what you’re currently getting in ImageJ % area of the nucleus that is heterochromatin spots is something you could do pretty easily in a CellProfiler pipeline but may or may not be directly calculable from your ImageJ workflow. Once you get started building a pipeline to analyze your images, if you have questions, please do reach back out on the forum.Īs far as the histogram, what are you actually making a histogram of? The pixel values within the whole image, the pixel values within the individual objects, the mean pixel value of each object, is it a line profile as hypothesized, etc? Some of these CellProfiler may be a direct replacement for, and some not. You can download the corresponding written tutorial on Translocation from the CellProfiler Github page. To get started using CellProfiler for analysis, we recommend watching this CellProfiler introductory workshop, which is available on the Center for Open Bioimage Analysis YouTube Channel. export the data using ExportToSpreadsheet and then test if there are differences between conditions using the software of your choice.add measurement modules such as MeasureObjectIntensity and MeasureObjectIntensityDistribution.segment the nuclei using the IdentifyPrimaryObjects module.The general workflow that I would try would be: I don’t know how to generate this type of histogram in CellProfiler, but you could still use the program to try to test if there is a difference in treated vs. You can learn about macros here: Introduction into Macro Programming - ImageJ This approach will work best if you can create an automated workflow within ImageJ to generate these histograms (that is, they don’t require manual input from the user). Then you can proceed with your fitting process as usual in order to differentiate between treated and untreated. One would be to create an ImageJ macro to automatically create your histograms and save them. I can think of a couple of approaches for this problem. I’m not exactly sure how you’re generating the histograms in ImageJ, but it sounds like you might be doing an intensity profile along a line in order to measure the intensity and position of heterochromatin in different conditions.
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