Plot Highly Correlated Feature Pairs — plot_feature

Creates scatter plots for pairs of features that have correlations outside specified thresholds. Each pair is displayed in a separate facet with its correlation coefficient.

Usage

plot_feature_correlations(
  data,
  variable,
  qc_types = NA,
  cor_min,
  cor_min_neg = -0.99,
  log_scale = FALSE,
  filter_data = FALSE,
  include_qualifier = FALSE,
  include_istd = FALSE,
  include_feature_filter = NA,
  exclude_feature_filter = NA,
  min_median_value = NA,
  point_size = 1,
  point_alpha = 0.8,
  point_stroke = 0.3,
  line_size = 0.5,
  line_color = "orange",
  line_alpha = 0.5,
  font_base_size = 8
)

Arguments

data: A data frame containing numeric columns for correlation analysis
variable: A character string indicating the variable to use for PCA analysis. Must be one of: "area", "height", "intensity", "norm_intensity", "response", "conc", "conc_raw", "rt", "fwhm".
qc_types: A character vector specifying the QC types to plot. It must contain at least one element. The default is NA, which means any of the non-blank QC types ("SPL", "TQC", "BQC", "HQC", "MQC", "LQC", "QC", "NIST", "LTR") will be plotted if present in the dataset.
cor_min: Numeric. Minimum correlation threshold. Only feature pairs with positive correlations above this value will be shown. Set to Inf to exclude positive corrections.
cor_min_neg: Numeric. Minimum nagative correlation threshold. Only feature pairs with negative correlations above this value will be shown. Set to -Inf to exclude nagative corrections.
log_scale: A logical value indicating whether to use a log10 scale for both axes. Default is FALSE.
filter_data: A logical value indicating whether to use all data (default) or only QC-filtered data (filtered via filter_features_qc()).
include_qualifier: A logical value indicating whether to include qualifier features. Default is TRUE.
include_istd: A logical value indicating whether to include internal standard (ISTD) features. Default is TRUE.
include_feature_filter: A character or regex pattern used to filter features by feature_id. If NA or an empty string ("") is provided, the filter is ignored. When a vector of length > 1 is supplied, only features with exactly these names are selected (applied individually as OR conditions).
exclude_feature_filter: A character or regex pattern used to exclude features by feature_id. If NA or an empty string ("") is provided, the filter is ignored. When a vector of length > 1 is supplied, only features with exactly these names are excluded (applied individually as OR conditions).
min_median_value: Minimum median feature value (as determined by the variable) across all samples from selected QC types that must be met for a feature to be included in the PCA analysis. NA (default) means no filtering will be applied. This parameter provides an fast way to exclude noisy features from the analysis. However, it is recommended to use filter_data with filter_features_qc().
point_size: A numeric value indicating the size of points in millimeters. Default is 1.
point_alpha: A numeric value indicating the transparency of points (0-1). Default is 0.8.
point_stroke: A numeric value indicating the stroke width of the points. Default is 0.3.
line_size: A numeric value indicating the size of the correlation line. Default is 0.5.
line_color: A character string indicating the color of the correlation line. Default is orange.
line_alpha: A numeric value indicating the transparency of the correlation line (0-1). Default is 0.5.
font_base_size: A numeric value indicating the base font size for plot text elements. Default is 8.

Value

A ggplot object showing scatter plots of highly correlated feature pairs. Returns NULL if no correlations meet the threshold criteria.