5 Bead Counts

5.1 Visualising Bead Counts

This tutorial focuses on creating plots to visualise the bead counts from your Luminex experimental data.

5.1.1 Setup

library(SeroTrackR)
library(tidyverse)

your_raw_data <- c(
  system.file("extdata", "example_MAGPIX_plate1.csv", package = "SeroTrackR"),
  system.file("extdata", "example_MAGPIX_plate2.csv", package = "SeroTrackR"), 
  system.file("extdata", "example_MAGPIX_plate3.csv", package = "SeroTrackR")
)
your_plate_layout <- system.file("extdata", "example_platelayout_1.xlsx", package = "SeroTrackR")

sero_data <- readSeroData(
  raw_data = your_raw_data, 
  platform = "magpix",        # default 
  version = "4.2"             # default 
)

plate_list <- readPlateLayout(
  plate_layout = your_plate_layout, 
  sero_data  = sero_data
)

qc_results  <- runQC(
  sero_data = sero_data,       # load in your serological data variable 
  plate_list = plate_list      # load your plate list variable 
)

5.1.2 Plot Bead Counts

The plotCounts() function provides a summary of the bead counts for each plate well are displayed, with blue indicating there are sufficient beads (≥15) or red when there are not enough. If any of the wells are red, they should be double-checked manually and re-run on a new plate if required.

plotCounts(qc_results, experiment_name = "experiment1")

getRepeats(qc_results, plate_list)

The getRepeats() function will inform you whether there are “No repeats necessary” or provide a list of samples to be re-run. In the example data, the beads in plate 2 wells A1 and A2 will need to be repeated.

Location	SampleID	Plate	QC
A1	Blank1	plate2	fail
A2	Blank2	plate2	fail

5.1.3 Plot Bead Counts per Antigen

This dot plot shows the raw bead counts for each antigen in each plate. This is intended as a quality control check to be able to identify which bead may be an issue.

plotBeadCounts(qc_results)

5.2 Customisations

For more customisations on how to manipulate your ggplot2 see the manual here or the book (Wickham 2016).

--- title: "Bead Counts" format: html --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) options(rmarkdown.html_vignette.check_title = FALSE) setup <- function() { needed <- c("knitr", "rmarkdown", "tidyverse", "kableExtra", "purrr") lapply(needed, function(pkg) { if (requireNamespace(pkg, quietly = TRUE)) { library(pkg, character.only = TRUE) } }) } setup() ``` ## Visualising Bead Counts This tutorial focuses on creating plots to visualise the bead counts from your Luminex experimental data. ### Setup ```{r setup 1} #| warning: false #| message: false library(SeroTrackR) library(tidyverse) your_raw_data <- c( system.file("extdata", "example_MAGPIX_plate1.csv", package = "SeroTrackR"), system.file("extdata", "example_MAGPIX_plate2.csv", package = "SeroTrackR"), system.file("extdata", "example_MAGPIX_plate3.csv", package = "SeroTrackR") ) your_plate_layout <- system.file("extdata", "example_platelayout_1.xlsx", package = "SeroTrackR") sero_data <- readSeroData( raw_data = your_raw_data, platform = "magpix", # default version = "4.2" # default ) plate_list <- readPlateLayout( plate_layout = your_plate_layout, sero_data = sero_data ) qc_results <- runQC( sero_data = sero_data, # load in your serological data variable plate_list = plate_list # load your plate list variable ) ``` ### Plot Bead Counts The `plotCounts()` function provides a summary of the bead counts for each plate well are displayed, with blue indicating there are sufficient beads (≥15) or red when there are not enough. If any of the wells are red, they should be double-checked manually and re-run on a new plate if required. ```{r} plotCounts(qc_results, experiment_name = "experiment1") ``` ```{r} #| exec: false #| eval: false getRepeats(qc_results, plate_list) ``` The `getRepeats()` function will inform you whether there are "No repeats necessary" or provide a list of samples to be re-run. In the example data, the beads in plate 2 wells A1 and A2 will need to be repeated. ```{r} #| echo: false getRepeats(qc_results, plate_list) %>% kable() %>% kable_styling(full_width = TRUE) ``` ### Plot Bead Counts per Antigen This dot plot shows the raw bead counts for each antigen in each plate. This is intended as a quality control check to be able to identify which bead may be an issue. ```{r} plotBeadCounts(qc_results) ``` ## Customisations For more customisations on how to manipulate your `ggplot2` see the manual [here](https://ggplot2.tidyverse.org/) or the book [@ggplot2].