sliwin {qpcR} | R Documentation |
A linear model is fit to a sliding window of the logarithmized raw fluorescence and the regression coefficient is calculated. At the point of maximum regression (log-linear range), the PCR efficiency is calculated.
sliwin(object, wsize = 5, border = 7, plot = TRUE)
object |
a 'drc' object. |
wsize |
the size of the sliding window, default is 5. |
border |
the -/+ border from the second derivative maximum cycle in which to do the fitting procedure. |
plot |
if TRUE the result is plotted, if FALSE the result is diplayed on the console. |
To avoid fits with a high R-squared in the baseline region, the second derivative maximum is taken as a fixpoint. This value is consequently always near to the exponential region of the data and avoids the problem above. The efficiency is calculated by E = exp(slope), as the transformed raw data was based on the natural logarithm. The initial template fluorescence (F0) is thus calculated by F0 = exp(intercept).
A list with the following components:
effmax |
the maximal PCR efficiency. |
rmax |
the maximum R-squared. |
init |
the initial template fluorescence F0. |
Andrej-Nikolai Spiess
Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data. Ramakers C et al., Neuroscience Letters, 2003, 339, 62-66.
m <- pcrfit(reps, 1, 2, l5()) sliwin(m)