Response data processing

Configure the processing of response data, for example, to subtract the absorbance of blank wells or to divide response values by the mean absorbance of maximum binding wells.

The following image from the 'Linear calibration curve (enhanced response data processing)' sample document shows a possible setup for the processing of response data. You can employ several adjustment and normalization steps and you can adjust the sequence of response data processing steps to your needs by drag and drop.

Note: This setup is intended to show all available response data processing methods. It is not intended as a recommendation for a setup in a productive system.
Figure 1. Response data processing setup for curve interpolation
Select the transformation method that is appropriate for your data. We support the following methods:
  • Adjustment
  • Normalization
  • Transformation
  • Replicate averaging

Adjustment

A fixed value or the mean response of a specific assay element is subtracted from every response value. You can apply adjustments to a group of assay elements (for example, Standard or Test), an individual assay element, or a specific plate.

Figure 2. Adjustment by a fixed value

Normalization

The response value is divided by a fixed value or the mean response of a specific assay element. You can apply normalizations to a group of assay elements (for example, Standard or Test), an individual assay element, or a specific plate.

Figure 3. Normalization by assay element scope

Transformation

The response value is transformed according to the function you select. You can employ logarithmic, square, and square root transformation functions.

Figure 4. Square root response transformation

Replicate averaging

The regression uses the average response of each dose step rather than the response values of individual replicates. As this method influences the degrees of freedom and the control limits, we recommend using it with care.

Figure 5. Activation of replicate averaging