Evaluate spectral demixing measurement
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Evaluate spectral demixing measurement

This usage example shows how to produce two-color images from spectrally unmixed data sets. It was written for an Alexa647/Alexa700 measurement on the Würzburg 1 biplane setup as documented in [Aufmkolk2012]. The first two tasks in this example produce prerequisite knowledge for the image generation, the alignment information (Produce linear alignment matrix) and the F2 ratios, i.e. the relative intensity of fluorophores between the channels.

Produce linear alignment matrix

We assume you have two input data files X1.tif and X2.tif showing 2 spectrally overlapping fluorophores. The images in both files are assumed to be synchronous, spectrally different views of the same sample area.

  1. Start rapidSTORM
  2. Set Input file to X1.tif

  3. Check Ignore libtiff warnings

    We use Andor SOLIS for recording, which records broken TIFF files.

  4. Set Size of input pixel to precalibrated value (107 nm)

  5. Go to the Expression filter output option and set Choose new output to Count localizations
  6. Start evaluation

  7. Enable the Minimum localization strength field and set its value very high, adjusting it until the second counter shows approximately as many localizations as the acquisition has frames.

    This ensures a sparse population of multi-fluorophore localizations in the output, which can easily be paired through the time coordinate. This is the "bead of opportunity" technique.

  8. Close the job
  9. Set Input file to X2.tif
  10. Repeat Step 6 to Step 8
  11. Open an alignment fitter job with Job->Alignment fitter->Minimal
  12. Set File 1 to X1.tif
  13. Set File 2 to X2.tif
  14. Set Output file to linMatrix_X1toX2.txt
  15. Set Sigma to 1
  16. Click Compute
  17. Wait for an alignment job to open and its progress bar to fill
  18. The final alignment matrix is displayed in the text fields. Check that it is sane, i.e. scale factors are close to 1, shear close to 0 and translation smaller than 2 micrometers
    • If the parameters are sane, this task is finished and the alignment matrix is stored in linMatrix_X1toX2.txt.
    • If the parameters are not sane, try a different setting of Sigma or different values in the Shift, Scale or Shear fields and repeat from step Step 16.

Analyze two-colour acquisition

We assume you have the same two input data files as in Produce linear alignment matrix and have a linear alignment matrix linMatrix_X1toX2.txt.

  1. Set user level to Intermediate
  2. Set Number of input channels to 2
  3. Select tab Channel 1 and set Input file to X1.tif

  4. Select tab Channel 2 and set Input file to X2.tif

    It is crucial to keep the channel naming

  5. Set Join inputs on to Spatially in z dimension
  6. Set Number of fluorophore types to 2
  7. In Input layer 2, set Plane alignment to Linear alignment
  8. In Input layer 2, set Plane Alignment file to linMatrix_X1toX2.txt

  9. Set Size of input pixel (107 nm) and PSF FWHM (370 and 390 nm, respectively) in both Input layer tabs

  10. Are the F2 ratios of the fluorophores already known?

    • No: Continue with Step 11
    • Yes: Run the evaluation and skip to Step 17
  11. Set the Transmission coefficient fields in both layers to the approximate relative brightnesses of the fluorophores. In this example, we estimated values of 2.5 and 0 for the first channel and 1 and 1 for the second channel.
  12. Go to the dSTORM engine output output and set Choose new output to Estimate PSF form
  13. Go to the Estimate PSF Form output and uncheck Fit PSF FWHM
  14. Run the evaluation
  15. A PSF selection window appears, showing the two channels in alternating rows. In each row pair, each column shows a pair of ROIs with a localization. The localizations are pre-classified as belonging to fluorophore 0 (red taint), 1 (green taint) or being ignored (grey taint). You can switch the classification by drawing a box around the image pair. When you are satisfied with the classification, close the window. The window reappears with new localizations until you have classified sufficiently many localizations. Make sure that both fluorophores are represented; if a particular fluorophore is overrepresented, switch it to ignored (grey taint).
  16. In the job tab, a tab box with the input layers shows the result of the PSF estimation once the form estimation is finished. Write down the new Transmission coefficient values for all tabs, these can be re-used in later evaluations.
  17. Wait for the evaluation to finish. The generated localizations file contains color-assigned localizations with the correct F2 values.

Produce a single two-colour image from two-colour localizations file

We assume that you have a localizations file with assigned colors X1.txt.

  1. Set Input File to X1.txt.
  2. Go to the Image display output and
    1. Set Colour palette for display to Vary hue with coordinate value
    2. Set Coordinate to vary hue with to fluorophore type
    3. Set Range of hue to 0.5 (cyan)
  3. Run the evaluation. The result image will be color-coded by fluorophore intensity.
  4. You can adjust the relative intensity by setting Value to assign to to amp and Expression to assign from to (fluo == 0) ? amp * 1.5 : amp, varying the 1.5 as necessary.

Produce two spectrally separated images from two-colour localizations file

We assume that you have a localizations file with assigned colors X1.txt.

  1. Set user level to Intermediate or higher
  2. Set Input File to X1.txt.
  3. Set Output file basename to X1-fluo1.
  4. Go to the Expression filter output and
    1. Set Value to assign to to Filter
    2. Set Expression to assign from to fluo == 0
  5. Run the evaluation, wait until it is finished and close the job
  6. Set Output file basename to X1-fluo2.
  7. Go to the Expression filter output and set Expression to assign from to fluo == 1
  8. Repeat Step 5
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