The best fit line can be determined by regression analysis. If software is unavailable, the ELISA data may be linearized by plotting the log of the concentrations versus the log of the O.D. Use the data reduction method that gives the best correlation value and backfit. They should read close to the expected values (+/- 10%). Next, treat standards as unknowns and interpolate the O.D. To do this, first plot the standard curve. One way to determine if the curve fit is correct is to backfit the standard curve O.D. linear, semi-log, log/log, 4 or 5 parameter logistic) be tried to see which curve best fits the ELISA data. If the recommended data reduction method is unavailable, it is recommended that various methods (e.g. When possible, utilize the recommended data reduction method specified in the assay protocol. Standard CurveĬreate a standard curve by reducing the data using computer software capable of plotting the mean absorbance (y axis) against the protein concentration (x axis). The coefficient of variation (CV) of duplicates should be ≤ 20%. This will provide enough data for statistical validation of the results.Īverage the duplicate or triplicate readings for each standard, control, and sample and subtract the average zero standard optical density (O.D.). If samples have been diluted, the concentration read from the standard curve must be multiplied by the dilution factor.Īlways run ELISA samples in duplicate or triplicate. When running an ELISA, the values of the unknown samples are assigned in relation to the standard curve.
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