efficiency: Amplification efficiency statistics and standard curves

Description

The efficiency function calculates amplification efficiency (E) and related statistics, including slope and coefficient of determination (R\(^2\)), and generates standard curves for qPCR assays.

Usage

efficiency(df, base_size = 12, legend_position = c(0.2, 0.2), ...)

Value

A list with the following components:

efficiency: A data frame containing slope, amplification efficiency (E), and R\(^2\) statistics for each gene.
Slope_compare: A table comparing slopes between genes.
plot: A ggplot2 object showing standard curves for all genes.

Arguments

df: A data frame containing dilution series and corresponding Ct values. The first column should represent dilution levels, and the remaining columns should contain Ct values for different genes.
base_size: font size
legend_position: legend position
...: Additional ggplot2 layer arguments

Author

Ghader Mirzaghaderi

Details

Amplification efficiency is estimated from standard curves generated by regressing Ct values against the logarithm of template dilution. For each gene, the function reports the slope of the standard curve, amplification efficiency (E), and R\(^2\) as a measure of goodness of fit. The function also provides graphical visualization of the standard curves.

Examples

Run this code


# Load example efficiency data
data <- read.csv(system.file("extdata", "data_efficiency1.csv", package = "rtpcr"))

# Calculate amplification efficiency and generate standard curves
efficiency(data)


ef <- read.csv(system.file("extdata", "data_efficiency_Yuan2006PMCBioinf.csv", package = "rtpcr"))
efficiency(ef)

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