nilseling
commented
2 years ago Hi @luglilab
So in the current implementation of the ImcSegmentationPipeline, hot-pixel filtering cannot be easily combined with histoCAT.
We are currently working on a framework that facilitates IMC data analysis. By using the tools provided below, you can export hot-pixel filtered images and import them into histoCAT.
Please have a look at the steinbock workflow. It allows you to run the CellProfiler pipeline as described in this repository within a containerised framework. Using steinbock, you can first filter the images and then export them for histoCAT import.
For more flexible data analysis: The output of steinbock as well as the output of the ImcSegmentationPipeline can be read into R using the imcRtools package. All further downstream analyses can be done in R using (i) recommended packages from the OSCA book, (ii) cytomapper and/or (iii) imcRtools.
Cheers,
Nils
Dear developer,
Looking at the imc_preprocessing.ipynb file, at the end, there is a third step in cellprofiler called 3_measure_mask_basic that is not needed when you perform downstream analysis in histocat. However, when running this last step in cellprofiler, the data analysis is not exactly the same as if I would use histocat. In the former, hot pixels are removed and intensities are scaled. In histocat, these steps are not performed, but instead data are transformed using arcsinh. What would be the best way to analyze the data?