Plot QC filtering summary by feature class
Source:R/plots-qc-filtering.R
plot_qc_summary_byclass.RdThis 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 = NULL,
legend_position = NULL,
legend_size = NULL,
show_legend_title = NULL,
title = NULL
)Arguments
- data
A
MRMhubExperimentobject.- font_base_size
Numeric. Base font size (in points) for plot text; all plot text scales proportionally with this value.
NULL(default) uses the global default set bymrmhub_set_plot_defaults()if one is in effect, otherwise an automatic size (derived from the facet-column count on paged plots, or the per-plot default shown in the Usage section above).- legend_position
Optional legend placement. One of
"right","left","top","bottom","none"; a corner keyword"inside-tr","inside-tl","inside-br","inside-bl"; or a numericc(x, y)in[0, 1]coordinates.NULL(default) keeps the current placement, unless a global default is set withmrmhub_set_plot_defaults().- legend_size
Optional single multiplier of
font_base_size(when<= 3) or absolute point size (when> 3) that scales the whole legend: text, title, key and the plotted symbols.NULL(default) leaves the legend unchanged.- show_legend_title
Logical.
NULL(default) keeps the legend title, unless a global default is set withmrmhub_set_plot_defaults();FALSEhides it,TRUEforces it shown.- title
Optional plot title.
NULL(default) orNAshows no title; a character string is shown as the title.
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_interference_correction(),
plot_matrixeffects(),
plot_normalization_qc(),
plot_pca(),
plot_pca_loading(),
plot_qc_interference_impact(),
plot_qc_summary_overall(),
plot_qcmetrics_comparison(),
plot_rla_boxplot(),
plot_rt_vs_chain(),
plot_runscatter(),
plot_runsequence()