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Plot PCA loadings

Source: R/plots-qc-pca.R
plot_pca_loading.Rd

Generates a plot of PCA loadings, illustrating the contribution of features to each principal component. This function can be used to investigate which feature (groups) are contributing to the variance seen in the plot and which need further investigation.

Usage

plot_pca_loading(
  data = NULL,
  variable,
  qc_types = NA,
  pca_dims = c(1, 2, 3, 4),
  log_transform = TRUE,
  top_n = 30,
  vertical_bars = FALSE,
  abs_loading = TRUE,
  filter_data = FALSE,
  include_qualifier = FALSE,
  include_istd = FALSE,
  include_feature_filter = NA,
  exclude_feature_filter = NA,
  min_median_value = NA,
  font_base_size = 7
)

Arguments

data

A MRMhubExperiment object

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", "NIST", "LTR") will be plotted if present in the dataset.

pca_dims

A numeric vector indicating for which PCA dimensions to the loadings should be shown. Default is c(1, 2, 3, 4).

log_transform

A logical value indicating whether to log-transform the data before the PCA. Default is TRUE.

top_n

Number of top features with highest absolute loading that will be to shown for each PC dimension. Default is 30.

vertical_bars

Show vertical bars instead of horizontal bars in the plot. Default is FALSE.

abs_loading

Show absolute loading values instead of signed loadings. Default is TRUE.

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().

font_base_size

A numeric value indicating the base font size for plot text elements. Default is 7.

Value

ggplot object with PCA loadings plot