Amplification efficiency statistics and standard curves

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)

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.

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.

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.

Author

Ghader Mirzaghaderi

Examples

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

# Calculate amplification efficiency and generate standard curves
efficiency(data)
#> $Efficiency
#>      Gene     Slope        R2        E
#> 1 C2H2.26 -3.388094 0.9965504 1.973110
#> 2 C2H2.01 -3.528125 0.9713914 1.920599
#> 3   GAPDH -3.414551 0.9990278 1.962747
#> 
#> $Slope_compare
#> $emtrends
#>  variable log10(dilutions).trend     SE df lower.CL upper.CL
#>  C2H2.26                   -3.39 0.0856 57    -3.56    -3.22
#>  C2H2.01                   -3.53 0.0856 57    -3.70    -3.36
#>  GAPDH                     -3.41 0.0856 57    -3.59    -3.24
#> 
#> Confidence level used: 0.95 
#> 
#> $contrasts
#>  contrast          estimate    SE df t.ratio p.value
#>  C2H2.26 - C2H2.01   0.1400 0.121 57   1.157  0.4837
#>  C2H2.26 - GAPDH     0.0265 0.121 57   0.219  0.9740
#>  C2H2.01 - GAPDH    -0.1136 0.121 57  -0.938  0.6186
#> 
#> P value adjustment: tukey method for comparing a family of 3 estimates 
#> 
#> 
#> $plot

#>