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

A MRMhubExperiment object.

font_base_size

Numeric. Base font size (in points) for plot text. Default is 8.

Value

A ggplot 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

Other QC plots: plot_feature_correlations(), plot_normalization_qc(), plot_pca(), plot_pca_loading(), plot_qc_interferences(), plot_qc_matrixeffects(), plot_qc_summary_overall(), plot_qcmetrics_comparison(), plot_rla_boxplot(), plot_rt_vs_chain(), plot_runscatter(), plot_runsequence()