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qpcR (version 1.3-9)

Modelling and analysis of real-time PCR data

Description

Model fitting, optimal model selection and calculation of various features that are essential in the analysis of quantitative real-time polymerase chain reaction (qPCR).

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Version

Install

install.packages('qpcR')

Monthly Downloads

1,597

Version

1.3-9

License

GPL (>= 2)

Maintainer

Andrej-Nikolai Spiess

Last Published

August 11th, 2014

Functions in qpcR (1.3-9)

The amplification efficiency curve of a fitted object

Calculation of Akaike weights/relative likelihoods/delta-AICs

Calculation of qPCR efficiency and other important qPCR parameters

Comparison of all sigmodal models within the exponential region

Calculation of qPCR efficiency by the 'linear regression of efficiency' method

Batch calculation of qPCR efficiency and other qPCR parameters

Calculation of PCR efficiency by fitting an exponential model

Workhorse function for qPCR model fitting

Residual sum-of-squares of a fitted model

Akaike's second-order corrected Information Criterion

Calculation of qPCR efficiency by the 'window-of-linearity' method

Root-mean-squared-error of a fitted model

An (overlayed) residuals barplot

Averaging of multiple reference genes

Advanced qPCR data import function

Plotting qPCR data with fitted curves/confidence bands/error bars

Error propagation using different methods

Simple qPCR data import function (i.e. from text files or clipboard)

Residual variance of a fitted model

Summarize measures for the goodness-of-fit

Allen's PRESS (Prediction Sum-Of-Squares) statistic, aka P-square

Combinatorial elimination of plateau and ground phase cycles

Calculation of ratios from qPCR runs with/without reference genes

Create nonlinear models from a dataframe and coerce them into a list

R-square value of a fitted model

Evidence ratio for model comparisons with AIC, AICc or BIC

Sigmoidal model selection by different criteria