Create a Z-Score Plot with Statistical Significance — CreateZScorePlot • SciDataReportR

This function generates a Z-score plot to compare multiple variables across different groups. It offers options for parametric or non-parametric tests, ordinal variable conversion, and custom labeling. Significant p-values and FDR-adjusted p-values are highlighted on the plot.

Usage

CreateZScorePlot(
  Data,
  TargetVar,
  Variables,
  VariableCategories = NULL,
  Relabel = TRUE,
  sort = TRUE,
  RemoveXAxisLabels = TRUE,
  Ordinal = TRUE,
  Parametric = TRUE,
  SigP_YCoord = 1.5,
  SigFDR_YCoord = 1.6
)

Arguments

Data: A dataframe containing the data to be analyzed.
TargetVar: A string specifying the column name of the grouping variable.
Variables: A vector of strings specifying the column names of the variables to be analyzed.
VariableCategories: An optional vector categorizing the variables.
Relabel: Logical; if TRUE, variables will be relabeled using their labels from the dataframe.
sort: Logical; if TRUE, variables will be sorted by category and p-value.
RemoveXAxisLabels: Logical; if TRUE, X-axis labels will be removed.
Ordinal: Logical; if TRUE, ordinal variables will be converted to numeric.
Parametric: Logical; if TRUE, parametric tests (t-test/ANOVA) will be used; otherwise, non-parametric tests (Wilcoxon/Kruskal-Wallis) will be used.
SigP_YCoord: Numeric; the y-coordinate for marking significant p-values.
SigFDR_YCoord: Numeric; the y-coordinate for marking significant FDR-adjusted p-values.

Value

A ggplot object representing the Z-score plot.