Retrieve QC bias and variability metrics — get_qc_bias

This function retrieves quality control (QC) bias and variability metrics from a MRMhubExperiment object. It returns a summary of QC metrics for specified QC samples, including bias, absolute bias, and intra-assay coefficient of variation (CV). The standard deviation of the concentration ratio is also included unless it is NA for all analytes, i.e. when no replicates were measured.

Usage

get_qc_bias_variability(
  data,
  qc_types = NA,
  sample_ids = NA,
  wide_format = "none",
  include_qualifier = FALSE,
  with_conc = TRUE,
  with_conc_target = TRUE,
  with_bias = TRUE,
  with_bias_abs = FALSE,
  with_conc_ratio = FALSE,
  with_cv_intra = TRUE,
  with_conc_out_of_range = TRUE,
  summary_table = FALSE
)

Arguments

data: A MRMhubExperiment object containing the dataset and necessary annotations for calibration analysis.
qc_types: A character vector specifying the QC types to include in the results, in addition to CAL. If not specified, all applicable QC types are included by default.
sample_ids: A character vector specifying the sample IDs to include in the results. If not specified, all analyses regardless of their sample IDs are included by default.
wide_format: Format of the output table. Must be one of "none", "features", or "samples". If "none", the output is in long format. If "features", the output is in wide format with features as columns. If "samples", the output is in wide format with samples as columns.
include_qualifier: Logical. If TRUE, includes qualifier features in the results. Defaults to FALSE.
with_conc: Logical. If TRUE, includes target and measured mean concentrations in the results. Defaults to TRUE.
with_conc_target: Logical. If TRUE, includes target (known) concentration of the QC sample in the results. Defaults to TRUE.
with_bias: Logical. If TRUE, includes percentage bias in the results. Defaults to TRUE.
with_bias_abs: Logical. If TRUE, includes absolute bias in concentration units in the results. Defaults to FALSE.
with_conc_ratio: Logical. If TRUE, includes the ratio of measured to target concentration in the results. Defaults to FALSE.
with_cv_intra: Logical. If TRUE, includes intra-assay coefficient of variation (CV) in the results. Defaults to TRUE.
with_conc_out_of_range: Logical. If TRUE (and the dataset carries the feature_conc_out_of_range flag from quantify_by_calibration()), includes the fraction of replicate measurements whose concentration fell outside the calibrated range (frac_conc_out_of_range). Defaults to TRUE.
summary_table: Logical. If TRUE, round the numeric metric columns to 3 significant figures for display (the integer replicate count n is left intact). This is a presentation view for reporting; the values are rounded, so do not use it for downstream computation. Defaults to FALSE (full, unrounded metrics).

Value

A data frame containing the calibration results, including metrics such as bias, percentage bias, and intra-assay CV based on specified parameters.

Details

The standard deviation of concentration is also included unless the number of replicates was 1.

The function uses data from the MRMhubExperiment object and filters it according to the specified QC types and other parameters. It then calculates summary statistics for each feature, such as bias and CV, and organizes the data into a user-specified format.