Plot Bead Count Data

This function gets the count data and plots the plate image, creating a new facet (i.e., panel) for each antigen and each line represents the different plates so that they can be visualised.

Usage

plotCounts(qc_results, experiment_name)

Arguments

qc_results

Output from `runQC()`.

experiment_name

User-input experiment name.

Value

Tile Plot showing binary result of "sufficient beads" with cut-off >15 beads and "repeat" less than or equal to 15 beads (ggplot).

Author

Shazia Ruybal-Pesántez, Dionne Argyropoulos

Examples

# \donttest{

# Step 0: Load example raw data
your_raw_data <- c(
  system.file("extdata", "example_MAGPIX_plate1.csv", package = "SeroTrackR"),
  system.file("extdata", "example_MAGPIX_plate2.csv", package = "SeroTrackR")
)
your_plate_layout <- system.file(
  "extdata",
  "example_platelayout_1.xlsx",
  package = "SeroTrackR"
)

# Step 1: Read serology data and plate layout
sero_data  <- readSeroData(your_raw_data,"magpix")
#> PASS: File example_magpix_plate1.csv successfully validated.
#> PASS: File example_magpix_plate2.csv successfully validated.
plate_list <- readPlateLayout(your_plate_layout, sero_data)
#> Plate layouts correctly identified!

# Step 2: Process counts and perform quality control
qc_results  <- runQC(sero_data, plate_list)

# Step 3: Plot Counts
plotCounts(qc_results, "experiment1")

# }