Quantitative Polymerase Chain Reaction (qPCR) Data Mining and Machine Learning Toolkit as Described in Burdukiewicz (2022) <doi:10.21105/Joss.04407>
armor: fetch errors gently
A function to test for autocorrelation of amplification curve data fro...
A function to get a decision (modus) from a vector of classes
A function to calculate the slope and intercept of an amplification cu...
A function to calculate numerous features from amplification curve dat...
A function to calculate to head to tail ratio of amplification curve d...
A function to calculate the slope and intercept of an amplification cu...
hookregNL - A function to calculate the slope of amplification curves ...
Human Rater 2.0
A function to perform a Local Robust Regression in Ranges defined by Q...
The datasets implemented in PCRedux
PCRedux - quantitative PCR Data Mining and Machine Learning Toolkit
pcrfit_single - A function to extract features from an amplification c...
Performance analysis for binary classification
A helper function to convert amplification curve data to the fdata for...
PCRedux app
A function to Group Amplification Curves According to their Shape
winklR: A function to calculate the angle based on the first and the s...
Extracts features from amplification curve data of quantitative Polymerase Chain Reactions (qPCR) according to Pabinger et al. 2014 <doi:10.1016/j.bdq.2014.08.002> for machine learning purposes. Helper functions prepare the amplification curve data for processing as functional data (e.g., Hausdorff distance) or enable the plotting of amplification curve classes (negative, ambiguous, positive). The hookreg() and hookregNL() functions of Burdukiewicz et al. (2018) <doi:10.1016/j.bdq.2018.08.001> can be used to predict amplification curves with an hook effect-like curvature. The pcrfit_single() function can be used to extract features from an amplification curve.
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