pcr (version 1.2.2)

pcr_assess: Assess qPCR data quality

Description

A unified interface to invoke different quality assessment methods of qPCR data.

Usage

pcr_assess(df, method = "standard_curve", ...)

Arguments

df

A data.frame of \(C_T\) values with genes in the columns and samples in rows rows. Each sample are replicates of a known input/dilution given by amount

method

A character string; 'standard_curve' (default) or 'efficiency' for invoking a certain quality assessment model

...

Arguments passed to the methods

Value

A data.frame or a plot. For details; pcr_standard and pcr_efficiency

Details

The different quality assessment methods can be invoked using the argument method with 'standard_curve' or 'efficiency'. Alternatively, the same methods can be applied by using the corresponding functions: pcr_standard or pcr_efficiency for calculating the amplification efficiency of a PCR reaction or the individual standard curves respectively. Unlike the amplification efficiency calculation when, using the double delta ct model, the standard curves are required in calculating the standard curve analysis model.

Examples

# NOT RUN {
#' # locate and read file
fl <- system.file('extdata', 'ct3.csv', package = 'pcr')
ct3 <- read.csv(fl)

# make amount/dilution variable
amount <- rep(c(1, .5, .2, .1, .05, .02, .01), each = 3)

# calculate the standard curve
pcr_assess(ct3,
           amount = amount,
           method = 'standard_curve')

# retrun a plot
pcr_assess(ct3,
           amount = amount,
           method = 'standard_curve',
           plot = TRUE)

# calculate amplification efficiency
pcr_assess(ct3,
           amount = amount,
           reference_gene = 'GAPDH',
           method = 'efficiency')

# return a plot
pcr_assess(ct3,
           amount = amount,
           reference_gene = 'GAPDH',
           method = 'efficiency',
           plot = TRUE)

# }