On the "Quantification" tab at "Settings > Peptide Settings", you can choose "Bilinear" in the "Regression Fit" dropdown.
When you choose "Bilinear", Skyline fits a piecewise linear equation to the data. That equation has a horizontal part, and a part with a positive slope.
This piecewise linear fit looks similar to the lower half of a sigmoid function.
I imagine you would need to have a lot of very precisely measured calibration points in order to be able to distinguish the lower half of a sigmoid from Skyline's bilinear fit.
Is the bilinear regression good enough? Or is it important to model the upper half of the sigmoid where it goes flat again above the upper limit of quantification?
-- Nick |
Dear Nick,
Thank you for your quick reply.
Similar to ELISA, the full sigmoidal curve can be used for quantification, as long as the method has been properly validated, a suitable fit model has been used, and the calibrators fall within their accuracy acceptance criteria (usually 80-120%).
I agree, that often only the lower part is of interest, but depending on the analyte and the assay, it is possible that the full curve is required.
I will check if the bilinear regression can be used for some of our analytes, i.e. those where only the lower part of the sigmoidal curve matters.
Are there other options than the bilinear regression?
Best,
Tobias |