Plot PCA or UMAP results on a 2D plane — hd_plot

hd_plot_dim() plots the sample data points on a 2D plane. The points can be plotted in the PCx/PCy or UMAP1/UMAP2 space.

Usage

hd_plot_dim(
  dim_object,
  metadata,
  x,
  y,
  color = NULL,
  palette = NULL,
  plot_loadings = NULL,
  nloadings = 5,
  axis_variance = TRUE
)

Arguments

dim_object: A PCA or UMAP object containing the results of the dimensionality reduction analysis. Created by hd_pca() or hd_umap().
metadata: An HDAnalyzeR object or a dataset in wide format and sample ID as its first column.
x: The name of the column in dim_object that contains the x-axis values.
y: The name of the column in dim_object that contains the y-axis values.
color: The name of metadata variable to be used to plot the points color.
palette: The color palette for the plot. If it is a character, it should be one of the palettes from hd_palettes().
plot_loadings: The component to be plotted. Default is NULL.
nloadings: The number of loadings to be plotted. Default is 5.
axis_variance: If TRUE, the explained variance of the components is added to the axis labels. Default is TRUE.

Value

A ggplot object

Examples

# Create the HDAnalyzeR object providing the data and metadata
hd_object <- hd_initialize(example_data, example_metadata)

# Run the PCA analysis and plot results
pca_object <- hd_pca(hd_object, components = 5, by_sample = TRUE, seed = 123) |>
  hd_plot_dim(hd_object, x = "PC1", y = "PC2", color = "Disease", palette = "cancers12")

pca_object$pca_plot


# Run the UMAP analysis and plot results
umap_object <- hd_umap(hd_object, components = 2, by_sample = TRUE, seed = 123) |>
 hd_plot_dim(hd_object, x = "UMAP1", y = "UMAP2", color = "Disease", palette = "cancers12")

 umap_object$umap_plot