Description Usage Arguments Details Value Author(s) References Examples
Calculates the efficiency curve from the fitted object by E_n = \frac{F_n}{F_{n-1}}, with E = efficiency, F = raw fluorescence, n = Cycle number. Alternatively, a cubic spline interpolation can be used on the raw data as in Shain et al. (2008).
1 2 |
object |
an object of class 'pcrfit'. |
method |
the efficiency curve is either calculated from the sigmoidal fit (default) or a cubic spline interpolation. |
sequence |
a 3-element vector (from, to, by) defining the sequence for the efficiency curve. Defaults to [min(Cycles), max(Cycles)] with 100 points per cycle. |
baseshift |
baseline shift value in case of |
smooth |
logical. If |
plot |
should the efficiency be plotted? |
For more information about the curve smoothing, baseline shifting and cubic spline interpolation for the method as in Shain et al. (2008), see 'Details' in maxRatio
.
A list with the following components:
eff.x |
the cycle points. |
eff.y |
the efficiency values at |
effmax.x |
the cycle number with the highest efficiency. |
effmax.y |
the maximum efficiency. |
Andrej-Nikolai Spiess
A new method for robust quantitative and qualitative analysis of real-time PCR.
Shain EB & Clemens JM.
Nucleic Acids Research (2008), 36, e91.
1 2 3 4 5 6 7 8 9 10 | ## With default 100 points per cycle.
m1 <- pcrfit(reps, 1, 7, l5)
eff(m1, plot = TRUE)
## Not all data and only 10 points per cycle.
eff(m1, sequence = c(5, 35, 0.1), plot = TRUE)
## When using cubic splines it is preferred
## to use the smoothing option.
#eff(m1, method = "spline", plot = TRUE, smooth = TRUE, baseshift = 0.3)
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