R: Modelling and Analysis of Real-Time PCR Data

# Modelling and Analysis of Real-Time PCR Data

## Documentation for package ‘qpcR’ version 1.4-2

- DESCRIPTION file
- Package NEWS

## Help Pages

AICc | Akaike's second-order corrected Information Criterion
akaike.weights | Calculation of Akaike weights/relative likelihoods/delta-AICs
b4 | The nonlinear/mechanistic models implemented in qpcR
b5 | The nonlinear/mechanistic models implemented in qpcR
b6 | The nonlinear/mechanistic models implemented in qpcR
b7 | The nonlinear/mechanistic models implemented in qpcR
batsch1 | The (published) datasets implemented in qpcR
batsch2 | The (published) datasets implemented in qpcR
batsch3 | The (published) datasets implemented in qpcR
batsch4 | The (published) datasets implemented in qpcR
batsch5 | The (published) datasets implemented in qpcR
boggy | The (published) datasets implemented in qpcR
calib | Calculation of qPCR efficiency using dilution curves and replicate bootstrapping
cm3 | The nonlinear/mechanistic models implemented in qpcR
competimer | The (published) datasets implemented in qpcR
Cy0 | Cy0 alternative to threshold cycles as in Guescini et al. (2008)
dil4reps94 | The (published) datasets implemented in qpcR
dyemelt | The (published) datasets implemented in qpcR
eff | The amplification efficiency curve of a fitted object
efficiency | Calculation of qPCR efficiency and other important qPCR parameters
evidence | Evidence ratio for model comparisons with AIC, AICc or BIC
expcomp | Comparison of all sigmodal models within the exponential region
expfit | Calculation of PCR efficiency by fitting an exponential model
expGrowth | The nonlinear/mechanistic models implemented in qpcR
expSDM | The nonlinear/mechanistic models implemented in qpcR
fitchisq | The chi-square goodness-of-fit
getPar | Batch calculation of qPCR fit parameters/efficiencies/threshold cycles with simple output, especially tailored to high-throughput data
guescini1 | The (published) datasets implemented in qpcR
guescini2 | The (published) datasets implemented in qpcR
htPCR | The (published) datasets implemented in qpcR
is.outlier | Outlier summary for objects of class 'modlist' or 'replist'
karlen1 | The (published) datasets implemented in qpcR
karlen2 | The (published) datasets implemented in qpcR
karlen3 | The (published) datasets implemented in qpcR
KOD | (K)inetic (O)utlier (D)etection using several methods
l4 | The nonlinear/mechanistic models implemented in qpcR
l5 | The nonlinear/mechanistic models implemented in qpcR
l6 | The nonlinear/mechanistic models implemented in qpcR
l7 | The nonlinear/mechanistic models implemented in qpcR
lievens1 | The (published) datasets implemented in qpcR
lievens2 | The (published) datasets implemented in qpcR
lievens3 | The (published) datasets implemented in qpcR
lin2 | The nonlinear/mechanistic models implemented in qpcR
linexp | The nonlinear/mechanistic models implemented in qpcR
llratio | Calculation of likelihood ratios for nested models
LOF.test | Formal lack-Of-Fit test of a nonlinear model against a one-way ANOVA model
LRE | Calculation of qPCR efficiency by the 'linear regression of efficiency' method
mak2 | The nonlinear/mechanistic models implemented in qpcR
mak2i | The nonlinear/mechanistic models implemented in qpcR
mak3 | The nonlinear/mechanistic models implemented in qpcR
mak3i | The nonlinear/mechanistic models implemented in qpcR
maxRatio | The maxRatio method as in Shain et al. (2008)
meltcurve | Melting curve analysis with (iterative) Tm identification and peak area calculation/cutoff
midpoint | Calculation of the 'midpoint' region
modlist | Create nonlinear models from a dataframe and coerce them into a list
mselect | Sigmoidal model selection by different criteria
parKOD | Parameters that can be changed to tweak the kinetic outlier methods
pcrbatch | Batch calculation of qPCR efficiency and other qPCR parameters
pcrboot | Bootstrapping and jackknifing qPCR data
pcrfit | Workhorse function for qPCR model fitting
pcrGOF | Summarize measures for the goodness-of-fit
pcropt1 | Combinatorial elimination of plateau and ground phase cycles
pcrsim | Simulation of sigmoidal qPCR data with goodness-of-fit analysis
plot.pcrfit | Plotting qPCR data with fitted curves
predict.pcrfit | Value prediction from a fitted qPCR model
PRESS | Allen's PRESS (Prediction Sum-Of-Squares) statistic, aka P-square
propagate | Error propagation using different methods
qpcR.news | Display news and changes of qpcR package versions
ratiobatch | Calculation of ratios in a batch format for multiple genes/samples
ratiocalc | Calculation of ratios from qPCR runs with/without reference genes
ratioPar | Calculation of ratios in a batch format from external PCR parameters
refmean | Averaging of multiple reference genes
replist | Amalgamation of single data models into a model containing replicates
reps | The (published) datasets implemented in qpcR
reps2 | The (published) datasets implemented in qpcR
reps3 | The (published) datasets implemented in qpcR
reps384 | The (published) datasets implemented in qpcR
resplot | An (overlayed) residuals barplot
resVar | Residual variance of a fitted model
RMSE | Root-mean-squared-error of a fitted model
Rsq | R-square value of a fitted model
Rsq.ad | Adjusted R-square value of a fitted model
RSS | Residual sum-of-squares of a fitted model
rutledge | The (published) datasets implemented in qpcR
sliwin | Calculation of qPCR efficiency by the 'window-of-linearity' method
spl3 | The nonlinear/mechanistic models implemented in qpcR
takeoff | Calculation of the qPCR takeoff point
testdat | The (published) datasets implemented in qpcR
update.pcrfit | Updating and refitting a qPCR model
vermeulen1 | The (published) datasets implemented in qpcR
vermeulen2 | The (published) datasets implemented in qpcR