Plot Levey-Jennings chart

The function plots a Levey-Jennings chart for the given analyte in the list of plates. The Levey-Jennings chart is a graphical representation of the data that enables the detection of outliers and trends. It is a quality control tool that is widely used in the laboratories across the world.

Usage

plot_levey_jennings(
  list_of_plates,
  analyte_name,
  dilution = "1/400",
  sd_lines = c(1.96),
  data_type = "Median"
)

Arguments

list_of_plates

A list of plate objects for which to plot the Levey-Jennings chart

analyte_name

(character(1)) the analyte for which to plot the Levey-Jennings chart

dilution

(character(1)) the dilution for which to plot the Levey-Jennings chart. The default is "1/400"

sd_lines

(numeric) the vector of coefficients for the standard deviation lines to plot, for example, c(1.96, 2.58) will plot four horizontal lines: mean +/- 1.96sd, mean +/- 2.58sd default is c(1.96) which will plot two lines mean +/- 1.96*sd

data_type

(character(1)) the type of data used plot. The default is "Median"

Value

A ggplot object with the Levey-Jennings chart

Examples

# creating temporary directory for the example
output_dir <- tempdir(check = TRUE)

dir_with_luminex_files <- system.file("extdata", "multiplate_reallife_reduced",
  package = "SerolyzeR", mustWork = TRUE
)
list_of_plates <- process_dir(dir_with_luminex_files,
  return_plates = TRUE, format = "xPONENT", output_dir = output_dir
)
#> Reading Luminex data from: /home/runner/work/_temp/Library/SerolyzeR/extdata/multiplate_reallife_reduced/IGG_CO_1_xponent.csv
#> using format xPONENT
#> Could not parse datetime string using default datetime format. Trying other possibilies.
#> Successfully parsed datetime string using order: mdY IM p
#> 
#> New plate object has been created with name: IGG_CO_1_xponent!
#> 
#> Processing plate 'IGG_CO_1_xponent'
#> Extracting the raw MFI to the output dataframe
#> Saving the computed MFI values to a CSV file located in: '/tmp/RtmpVDBVCM/IGG_CO_1_xponent_MFI.csv'
#> Fitting the models and predicting RAU for each analyte
#> Saving the computed RAU values to a CSV file located in: '/tmp/RtmpVDBVCM/IGG_CO_1_xponent_RAU.csv'
#> Computing nMFI values for each analyte
#> Saving the computed nMFI values to a CSV file located in: '/tmp/RtmpVDBVCM/IGG_CO_1_xponent_nMFI.csv'
#> Reading Luminex data from: /home/runner/work/_temp/Library/SerolyzeR/extdata/multiplate_reallife_reduced/IGG_CO_2_xponent.csv
#> using format xPONENT
#> Could not parse datetime string using default datetime format. Trying other possibilies.
#> Successfully parsed datetime string using order: mdY IM p
#> 
#> New plate object has been created with name: IGG_CO_2_xponent!
#> 
#> Processing plate 'IGG_CO_2_xponent'
#> Extracting the raw MFI to the output dataframe
#> Saving the computed MFI values to a CSV file located in: '/tmp/RtmpVDBVCM/IGG_CO_2_xponent_MFI.csv'
#> Fitting the models and predicting RAU for each analyte
#> Saving the computed RAU values to a CSV file located in: '/tmp/RtmpVDBVCM/IGG_CO_2_xponent_RAU.csv'
#> Computing nMFI values for each analyte
#> Saving the computed nMFI values to a CSV file located in: '/tmp/RtmpVDBVCM/IGG_CO_2_xponent_nMFI.csv'
#> Reading Luminex data from: /home/runner/work/_temp/Library/SerolyzeR/extdata/multiplate_reallife_reduced/IGG_CO_3_xponent.csv
#> using format xPONENT
#> Could not parse datetime string using default datetime format. Trying other possibilies.
#> Successfully parsed datetime string using order: mdY IM p
#> 
#> New plate object has been created with name: IGG_CO_3_xponent!
#> 
#> Processing plate 'IGG_CO_3_xponent'
#> Extracting the raw MFI to the output dataframe
#> Saving the computed MFI values to a CSV file located in: '/tmp/RtmpVDBVCM/IGG_CO_3_xponent_MFI.csv'
#> Fitting the models and predicting RAU for each analyte
#> Saving the computed RAU values to a CSV file located in: '/tmp/RtmpVDBVCM/IGG_CO_3_xponent_RAU.csv'
#> Computing nMFI values for each analyte
#> Saving the computed nMFI values to a CSV file located in: '/tmp/RtmpVDBVCM/IGG_CO_3_xponent_nMFI.csv'
list_of_plates <- rep(list_of_plates, 10) # since we have only 3 plates i will repeat them 10 times

plot_levey_jennings(list_of_plates, "ME", dilution = "1/400", sd_lines = c(0.5, 1, 1.96, 2.58))