-
Using a linear curve fit (or regression) in Excel (y = mx + c)
- Excel is an extremely powerful tool designed for a wide range of applications but drawing standard curves and interpolating unknown concentrations for ELISAs assays is not one of them. Bioassays or immunoassays resulting from biological systems follow a trend that is more analogous to the four paramater logistic (4PL) or five parameter parameter logistic (5PL) models rather than a linear model because there are limits to every biological system whereas linear curve fits go to infinity.
- Simply plugging in 0.5 for y and solving for x using a linear equation will get you the midpoint of the line but it is not an accurate IC50 or EC50 value because we are starting off with a very crude equation or approximation of the true curve fit. Simply put, you are forcing a square peg into a round hole. The more accurate method of obtaining the IC50 or EC50 value would be to use the 4PL model equation to do the curve fit and using the calculated C parameter.
- Excel is an extremely powerful tool designed for a wide range of applications but drawing standard curves and interpolating unknown concentrations for ELISAs assays is not one of them. Bioassays or immunoassays resulting from biological systems follow a trend that is more analogous to the four paramater logistic (4PL) or five parameter parameter logistic (5PL) models rather than a linear model because there are limits to every biological system whereas linear curve fits go to infinity.
-
Using the trendline feature with a scatter plot in Excel to get the equation and parameter values
- Excel only offers linear, logarithmic, polynomial, power, exponential, and moving average as options for the trendline (reference). None of these are sufficient enough to describe the sigmoidal shape of immuno and bioassays.
-
Drawing standard curves without using weighting to offset heteroscedasticity
- Heteroscedasticity is a phenomenon in which the variance of the dependent variable varies across the data. When dealing with [MFI/absorbance values/RLU] and concentration values, the concentrations usually increase as the [MFI/absorbance values/RLU] increases. When dealing with the high end of the standard curve, it is natural for the concentration values to have a greater variance when compared to the small concentration values on the low end of the standard curve. The use of weighting algorithms such as 1/y or 1/y^2 can be used to deal with the variance. More details can be found here.
The correct way of doing 4PL curve fits in Excel usually involve having to install an add-on that can do 4PL curve fitting but not all add-ons support weighting.
ReaderFit provides 4PL and 5PL curve fits with 4 different weighting algorithms.
ReaderFit.com – Free online curve-fitting application
Sign Up for Free Account
ReaderFit Desktop – Robust curve-fitting, quality control and reporting desktop software
Download Free Trial







