plot_basic_lab_qc: Generate Basic LAB QC Plots

In MoTrPAC/MotrpacBicQC: QC/QA functions for the MoTrPAC community

Generate Basic LAB QC Plots

Description

This function creates a set of four QC plots for an LAB assay. The plots include:

• An overall value distribution histogram with a density overlay and missing value percentage.

• A boxplot comparing value distributions across sample types.

• A scatter plot with a loess smooth showing the trend of values over injection or sample order.

• A bar plot summarizing the percentage of missing data by sample type.

Usage

plot_basic_lab_qc(
  results,
  results_long,
  out_qc_folder = NULL,
  output_prefix,
  printPDF = TRUE,
  verbose = TRUE
)

Arguments

results	A data frame containing assay results. Expected to have one row per analyte, with columns such as analyte_name and other metadata.
results_long	A long-format data frame containing sample-level data. Expected columns include: sample_id, sample_type, value, sample_order, and sample_id_ordered.
out_qc_folder	Character. The folder where QC plot PDFs will be saved. If NULL, the function will create a default folder.
output_prefix	Character. A prefix to be used in the names of output PDF files.
printPDF	Logical. If TRUE, the function outputs the plots to PDF files.
verbose	Logical. If TRUE, the function prints progress messages to the console.

Details

The function uses ggplot2 syntax to generate clean and informative plots, avoiding clutter even with large numbers of samples (e.g., > 1400 samples). It calculates an overall missing value percentage for the measured values, and provides visual summaries of the data distribution and missing data prevalence.

Value

Invisibly returns a gridExtra::grid.arrange object containing the arranged plots. The primary output is the saved PDF file(s) if printPDF = TRUE.

MoTrPAC/MotrpacBicQC documentation built on April 11, 2025, 7:51 p.m.