Function reference • DoubleqpcR

All functions
`Cq.data.df()`	This Function will give the data.cq samples for one Cq type in a dataframe helper function.
`Cq.data.mean()`	This Function will summarize the data.cq samples for one Cq type! helper function.
`calc.Cq()`	calculates Cq values
`calc.Cq.qpcR()`	calculates Cq values
`combineSubsamples()`	This Function will combine subsamples, so that they can be used as one sample.
`delta.Cq.data()`	This Function will give the delta Cq values. Always: offtarget Cq - target Cq helper function.
`linSqrtTransform()`	This Function will linearise the Delta Cq data with a shifted square root transformation. helper function.
`make.Cq.data()`	This Function will create the main Data object for all analysis. Used after an input is created with read.CqTable and all optional calculation data validation is complete.
`plot.Cq()`	plots Cq values with the both genotypes on x and y axis
`plot.Cq.efficiency()`	plots Cq values of each genotype againgst the pseudo log concentration.
`plot.curve()`	plot fluorescence curves
`plot.delta.Cq.box()`	plots delta Cq values as box-plots
`plot.delta.Cq.differences()`	plots delta Cq values against the square root of the concentration
`plot.delta.Cq.overview()`	plots delta Cq values against the concentration
`reTransform()`	This Function will retransform a value / list etc to normal percentage / proportion
`read.cqTable()`	Load cq table
`read.fluorescenceTable()`	Load fluorescence table
`regression.delta.Cq()`	This function will build a regression model on the delta Cq values. Plot and cross validation is included.
`table.Cq()`	shows Cq values from a sample and the mean Delta Cq
`voges_dixon()`	Helper function for outlier detection.
`voges_grubbs()`	Helper function for outlier detection.

Reference

All functions