I’ll take each of these in order:
(1) Assay experiment quality: The CalculateStatistics module generates the V and Z’ factors for all measurements made by the pipeline. But not all these factors are relevant for a translocation assay. (a) OrigThreshold and Threshold are used to segment the cells from the background (b) ObjectCount are the number of objects found in a given image. © Classify comes from the ClassifyObjects module which separates measurements into bins based on a metric (d) Children comes from the IdentifySecondary module which produces the cell boundaries. (d) Correlation, Intensity, AreaShape and Texture come from the Calculate modules of those names. For a translocation assay, you will probably be interested in (d).
(2) Percentage of cells with nuclear translocation: Ratio1 gives you the blue-to-green florescence proportion on a object-by-object basis in the Excel file. The threshold for what ratio value counts as sufficient translocation for a particular cell is up to your judgment. Once you decide this, you can count cells above and below this threshold for a given dose, and come up with a curve much like Figure 4b in the Genome Biology paper I mentioned previously.
(3) channel1ILLUM.mat and channel2ILLUM.mat. These are illumination correction image files. Since in microscopy, there is commonly uneven background illumination. If it is not accounted for and corrected, it may distort the fluorescence values leading to incorrect quantification.
The modules CorrectIlluminationCalculate and CorrectIlluminationApply deal with this, and are incorporated in the additional file ExampleSBSIlluminationPIPE.mat that should be in the same directory as the SBS images. The result of this pipeline are the ILLUM.mat files which are then used by ExampleSBSPIPE.mat. Since you ran the ExampleSBSPIPE pipeline successfully, I assume that you found them (or at least the pipeline did)? If you don’t have them, you can get them with the rest of the files: cellprofiler.org/linked_files/Ex … Images.zip
You will need to create illumination files for your particular red and green images. Have a look at the ExampleSBSIlluminationPIPE pipeline to see how it works, and how the two channels are fed in.
(4) Interpretation of graph. The amount of the SBS dose is given by the ‘SBS dose’ bar. The amount of translocation increases with increasing SBS dose. The way you can see this is looking at the correlation between the nuclear fluorescence in the blue and green channels, as shown by the red bar.
For the low does, protein is exported out of the nuclei so the nuclei are bright in the nuclei channel (Channel1: blue) but dark in the GFP channel (Channel2: green). Hence the fluorescence in CorrBlue and CorrGreen are anti-correlated and is negative. At the higher doses, export is blocked and protein accumulates in the nucleus, so the nuclei are bright in both channels. Hence, CorrBlue and CorrGreen are positively correlated.
Note that this graph comes from the Image Excel file, which means that it is averaged over all nuclei in that image. If you want to see the individual nuclei data, you need to see the Excel file for Nuclei (as mentioned for #2).
Hope this helps,