Plot QC Filtering Summary by Feature Class

This function provides a summary of feature QC filtering based on feature class, showing the number of features that passed or failed various quality control criteria. It visualizes the filtering in a hierarchical sequence. Features are first evaluated against lower-level filters such as signal-to-blank (S/B) ratios and limit of detection (LOD), followed by higher-level filters like the coefficient of variation (CV) or linear regression results. This means that a feature is classified as failing a given criterion (e.g., CV) only if it has passed all hierarchically lower filters (e.g., S/B ratio and LOD).

Usage

plot_qc_summary_byclass(data = NULL, font_base_size = 8)

Arguments

data

MidarExperiment object

font_base_size

The base font size for the plot. Default is 8.

Value

A ggplot2 object showing the feature QC filtering summary by feature class.

See also

plot_qc_summary_overall for an overall summary plot filter_features_qc for comparing QC metrics