Plot the log of library quantities vs Ct

Usage

pcr_lib_qc_plot_slope(lib_qc)

Arguments

lib_qc: Output of pcr_lib_qc

Value

a ggplot

Details

An optimal plot will have a slope of -3.32. This is because we expect that a sample 10x more concentrated than another will reach the same abundance in 3.32 doublings FASTER (that is, 3.32 fewer doubles, or Cts). Therefore, for each 10x increase in concentration (one point left to right on the plot) we expect a decrease in CT of 3.32. A steeper slope (more negative) implies a poorer efficiency (more cycles are required to reach 10x than perfect doubling would imply)

Examples

system.file("extdata", "untidy-standard-curve.xlsx", package = "amplify") |>
  pcr_tidy(pad_zero = TRUE) |>
  pcr_lib_calc() |>
  pcr_lib_qc() |>
  pcr_lib_qc_plot_slope()
#> Error in pcr_tidy(system.file("extdata", "untidy-standard-curve.xlsx",     package = "amplify"), pad_zero = TRUE): could not find function "pcr_tidy"