qpcR (version 1.0-6)

expfit2: Calculation of PCR efficiency by fitting of an exponential model after outlier cycle detection

Description

The outlier cycles (and thus the region when the PCR curve rises significantly above background) are identified by the studentized residual method as in Tichopad et al. (2003). An exponential model is then fit to the next defined number of cycles.

Usage

expfit2(object, fitcyc = 5, plot = TRUE, pval = 0.01, ...)

Arguments

object

a 'drc' object.

fitcyc

the number of cycles used for exponential fitting.

plot

if TRUE the result is plotted, if FALSE the result is diplayed on the console.

pval

the p-value for the outlier significance of the studentized residuals.

...

other arguments to be passed to multdrc.

Value

• A list with the following components:
• outlier
  the outlier cycle.
• Eff.fit
  the PCR efficiency calculated from the exponential fit.
• Eff.curve
  the PCR efficiency for each cycle within the exponential phase. See Details.
• resVar
  the residual variance of the fit.
• AIC
  the Akaike Information Criterion of the fit.
• RMSE
  the root-mean-squared-error of the fit.
• init
  the initial template fluorescence, i.e. 'F0'.
• mod
  the exponential model from the best fit.

Details

The exponential growth function f(x) = b * exp(d * x) + e is fit to the data. Calls outlier and studres for calculation of the studentized residuals and definition of the outlier cycles. The efficiency is calculated a) from the exponential fit with $E = exp(d)$ (Eff.fit) and b) for each cycle within the exponential region from the raw fluorescence values by $E = \frac{F(n)}{F(n-1)}$ (Eff.curve). The inital template fluorescence (F0) is derived from parameter b. If the detection of outlier cycles is problematic (i.e. due to high noise), one can improve results by lowering the p-value.

References

Standardized determination of real-time PCR efficiency from a single reaction set-up. Tichopad et al., Nucleic Acids Research, 2003, e122.

Examples

m <- multdrc(F1.1 ~ Cycles, data = reps, fct = l5())
expfit2(m)