Comparison of two feature QC metrics variables

This function generates scatter plots comparing two QC metrics variables across feature classes. A list of available QC metrics is available from the calc_qc_metrics() documentation.

Usage

plot_qcmetrics_comparison(
  data = NULL,
  plot_type,
  x_variable,
  y_variable,
  qc_types = NA,
  facet_by_class = FALSE,
  y_shared = FALSE,
  filter_data = FALSE,
  include_qualifier = FALSE,
  equality_line = FALSE,
  threshold_values = NA_real_,
  log_scale = FALSE,
  x_lim = c(NA_real_, NA_real_),
  y_lim = c(NA_real_, NA_real_),
  cols_page = 5,
  point_size = NULL,
  point_alpha = 0.5,
  point_color = "#0460acff",
  point_fill = "#4da2e7ff",
  point_shape = 21,
  point_stroke = 0.5,
  font_base_size = NULL,
  autoscale = TRUE,
  legend_position = NULL,
  legend_size = NULL,
  show_legend_title = NULL,
  title = NULL,
  strip_text_size = NULL,
  strip_bg_color = NULL,
  legend_bg_alpha = NULL
)

Arguments

data: A MRMhubExperiment object.
plot_type: A character string specifying the type of plot to generate. Must be one of "scatter", "diff", or "ratio". Selecting "scatter" plots the "y_variable" against the "x_variable" values as a scatter plot, "diff" plots the difference between the two values against the average value, and "ratio" plots the log2 ratio of the two values against the average value.
x_variable: The name of the QC metric variable to be plotted on the x-axis.
y_variable: The name of the QC metric variable to be plotted on the y-axis.
qc_types: A character vector specifying the QC types to plot.
facet_by_class: Logical; if TRUE, facets the plot by feature_class, as defined in the feature metadata.
y_shared: Logical; if TRUE, all facets share the same y-axis scale. If FALSE (default), each facet has its own y-axis scale.
filter_data: Logical; whether to use all data (default) or only QC-filtered data (filtered via filter_features_qc()).
include_qualifier: Logical; whether to include qualifier features (default is TRUE).
equality_line: Logical; whether to show a line indicating identical values in both compared variables (default is FALSE).
threshold_values: Numeric single value or vector with 2 elements; threshold valus to be shown as dashed lines from both axes on the plot (default is NA).
log_scale: Logical, whether to use a log10 scale the axes.
x_lim: Numeric vector of length 2 for x-axis limits. Use NA for auto-scaling (default is c(0, NA)).
y_lim: Numeric vector of length 2 for y-axis limits. Use NA for auto-scaling (default is c(0, NA)).
cols_page: Integer; number of facet columns per page (default is 5).
point_size: Numeric; size of points in millimeters (default is 1).
point_alpha: Numeric; transparency of points (default is 0.5).
point_color: A vector specifying the colors for points corresponding to different QC types. This can be either an unnamed vector or a named vector, with names corresponding to QC types. Unused colors will be ignored. Default is NA which corresponds to the default colors for QC types defined in the package.
point_fill: A vector specifying the fill colors for points corresponding to different QC types. This can be either an unnamed vector or a named vector, with names corresponding to QC types. Unused fill colors will be ignored. Default is NA which corresponds to the default fill colors for QC types defined in the package.
point_shape: A vector specifying the shapes for points corresponding to different QC types. This can be either an unnamed vector or a named vector, with names corresponding to QC types. Unused shapes will be ignored. Default is NA which corresponds to the default shapes for QC types defined in the package.
point_stroke: Numeric; thickness of point borders (default is 0.5).
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 by mrmhub_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).
autoscale: Logical. When TRUE (default), font_base_size and point_size left as NULL are sized automatically from cols_page (more facet columns per page give smaller text and points). Any value passed explicitly always takes precedence. When FALSE, unset sizes fall back to the single-plot defaults.
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 numeric c(x, y) in [0, 1] coordinates. NULL (default) keeps the current placement, unless a global default is set with mrmhub_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 with mrmhub_set_plot_defaults(); FALSE hides it, TRUE forces it shown.
title: Optional plot title. NULL (default) or NA shows no title; a character string is shown as the title.
strip_text_size: Optional facet strip text size, as a multiplier of font_base_size (when <= 3) or an absolute point size (when > 3). NULL (default) inherits from font_base_size.
strip_bg_color: Optional facet strip background fill colour. The strip text colour is set automatically for contrast (white on a dark fill, black on a light one). NULL (default) keeps the house dark-navy strips.
legend_bg_alpha: Optional opacity ([0, 1]) of a white legend background box, useful for a readable inside legend drawn over points. NULL (default) leaves the legend background unchanged.

Value

A ggplot object representing the scatter plot.

Details

The comparison is visualized through one of three plot types:

Scatter plot: Values of y_variable vs x_variable
Difference plot: (y_variable - x_variable) vs mean of both values
Ratio plot: log2(y_variable / x_variable) vs mean of both values

x_variable and y_variable must be available in the QC metrics table. Please refer to the help page of calc_qc_metrics() for more information on the available QC metric variables.
When facet_by_class = TRUE, then the feature_class must be defined in the metadata or retrieved via specific functions, e.g., parse_lipid_feature_names().

Usage

Arguments

Value

Details

See also