... | @@ -52,20 +52,18 @@ Here we explain how to install and use Fluorescence Correlation Spectroscopy (FC |
... | @@ -52,20 +52,18 @@ Here we explain how to install and use Fluorescence Correlation Spectroscopy (FC |
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In Python View node of calibration plot users have an opportunity to:
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In Python View node of calibration plot users have an opportunity to:
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* Pick the point of interest in the calibration plot window to see fluctuation and correlation data from the respective FCS position. The line can be influenced by outliers (see step 8 in the Procedure section)
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* Pick the point of interest in the calibration plot window to see fluctuation and correlation data from the respective FCS position. The line can be influenced by outliers (see step 8 in the Procedure section)
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> Sensitivity of picking event can be adjusted in the plot parameters input
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* Check the statistics parameters and level of bleaching at the headings of plots.
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* Check the statistics parameters and level of bleaching at the headings of plots.
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* Move and zoom a working space
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* Move and zoom a working space
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* Adjust spacing and the view of axes and curves
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* Adjust spacing and the view of axes and curves
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* Save the image of the plot
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* Save the image of the plot
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8. Delete points that haven't passed Quality Check (the points with "bad" fluctuations or poor quality of fitting.
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8. Quality Check <br>
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Delete points that haven't passed Quality Check (the points with "bad" fluctuations or poor quality of fitting)
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* List the points to delete in plot parameters input. <br>
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* List the points to delete in plot parameters input. <br>
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**Important note**: The Standart Quality check does **not guarantee** to remove all "bad" fluctuations. Thus we recommend going through calibration points and remove all "bad" fluctuations manually. To delete the points in calibration plot, fill the numbers from the annotations of corresponding points into plot parameter input (points to delete). Reexecute the Python View node with calibration plot
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**Important note**: The Standart Quality check does **not guarantee** to remove all "bad" fluctuations. Thus we recommend going through calibration points and remove all "bad" fluctuations manually. To delete the points in the calibration plot, fill the numbers from the annotations of corresponding points into plot parameter input (points to delete). Reexecute the Python View node with calibration plot
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> This step could also help to get rid of outliers that can influence the liner parameters of the calibration line.
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> This step could also help to get rid of outliers that can influence the liner parameters of the calibration line.
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#### Interactive Visualisation
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> Sensitivity of picking event can be adjusted in the plot parameters input.
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![calibration2](uploads/9515b50eb8729b4665a7b53b2b8852b2/calibration2.png)
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![calibration2](uploads/9515b50eb8729b4665a7b53b2b8852b2/calibration2.png)
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#### Output files
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#### Output files
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