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Plot the magnitude of interference correction as a histogram

Source: R/plots-qc-interference.R
plot_qc_interference_impact.Rd

Shows how many features were affected by which magnitude of interference correction, as a histogram of the per-feature correction impact (percent of raw signal removed) within one or more QC types (study samples by default). The data must already be interference-corrected. Features with no impact are excluded and reported.

Usage

plot_qc_interference_impact(
  data,
  qc_types = "SPL",
  include_qualifier = FALSE,
  include_istd = TRUE,
  include_feature_filter = NA,
  exclude_feature_filter = NA,
  min_correction_pct = NA,
  binwidth = NA,
  font_base_size = 8
)

Arguments

data

A MRMhubExperiment (already interference-corrected).

qc_types

QC type(s) to summarize. Default "SPL" (study samples). Set to NA to use all non-blank sample/QC types.

include_qualifier

Include qualifier features. Default FALSE.

include_istd

Include internal standards. Default TRUE.

include_feature_filter

Feature(s) to include by feature_id, as a character vector. Each element is matched exactly when it names an existing feature, otherwise treated as a regex; elements combine with OR. A full ID (e.g. "S1P d18:0 [M>60]") needs no escaping, while patterns like "PC|PE" still work. NA or "" ignores the filter.

exclude_feature_filter

Feature(s) to exclude by feature_id, matched the same way as include_feature_filter. NA or "" ignores the filter.

min_correction_pct

Keep only features whose median correction (percent of raw signal removed) is at least this value. NA (default) keeps every feature with a positive impact. Use to drop negligible corrections.

binwidth

Histogram bin width (percent). Default NA (30 bins).

font_base_size

Base font size. Default 8.

Value

A ggplot object: feature count vs. percent of signal removed.

See also

Other QC plots: plot_feature_correlations(), plot_interference_correction(), plot_matrixeffects(), plot_normalization_qc(), plot_pca(), plot_pca_loading(), plot_qc_summary_byclass(), plot_qc_summary_overall(), plot_qcmetrics_comparison(), plot_rla_boxplot(), plot_rt_vs_chain(), plot_runscatter(), plot_runsequence()