PCA plot — get_pca_plot • VISTA

Uses normalized counts to compute principal components and plot samples, optionally restricting to selected groups or genes.

Usage

get_pca_plot(
  x,
  sample_group = NULL,
  group_column = NULL,
  genes = NULL,
  top_n_genes = NULL,
  label = FALSE,
  label_size = 3,
  point_size = 10,
  shape_by = NULL,
  shape_values = NULL,
  sample.seed = 123,
  show_clusters = FALSE,
  color_by = NULL,
  use_vista_colors = NULL,
  palette = NULL,
  colors = NULL,
  use_group_colors = TRUE
)

Arguments

x: A VISTA object containing normalized counts.
sample_group: Optional character vector of group labels (taken from the column specified by group_column, defaulting to the stored grouping column) used to subset samples prior to PCA. Use NULL to include all samples.
group_column: Optional column name in sample_info to use for grouping. Defaults to the stored grouping column.
genes: Optional character vector of gene identifiers to restrict the PCA input matrix. When NULL, all genes are used.
top_n_genes: Optional integer selecting the top most variable genes to include. Ignored when genes is supplied.
label: Logical; if TRUE, sample names are drawn next to the points.
label_size: Numeric size of sample labels when label = TRUE.
point_size: Numeric size of the plotted points.
shape_by: Optional column name in sample_info used to map point shape. When NULL, shapes are not mapped.
shape_values: Optional vector of shapes passed to scale_shape_manual() when shape_by is set. Use a named vector to map shapes to specific levels.
sample.seed: Deprecated/unused; retained for backward compatibility.
show_clusters: Logical; add normal ellipses per group when TRUE.
color_by: Optional column name in sample_info used to map point colour. Defaults to the active grouping column.
use_vista_colors: Deprecated alias for use_group_colors. When supplied, it overrides use_group_colors.
palette: Optional qualitative palette name used when generating colours for non-group metadata levels.
colors: Optional named character vector of manual colours overriding both palette and stored VISTA colours.
use_group_colors: Logical; when TRUE, prefer the stored VISTA group colours when colouring by the grouping column.

Value

A ggplot object showing the first two PCs.

Examples

# Create VISTA object
data("count_data", package = "VISTA")
data("sample_metadata", package = "VISTA")

vista <- create_vista(
  counts = count_data[1:200, ],
  sample_info = sample_metadata[1:6, ],
  column_geneid = "gene_id",
  group_column = "cond_long",
  group_numerator = "treatment1",
  group_denominator = "control"
)
#> estimating size factors
#> estimating dispersions
#> gene-wise dispersion estimates
#> mean-dispersion relationship
#> final dispersion estimates
#> fitting model and testing

# Basic PCA plot
get_pca_plot(vista)


# With sample labels
get_pca_plot(vista, label = TRUE)


# Using top variable genes
get_pca_plot(vista, top_n_genes = 100)


# With confidence ellipses
get_pca_plot(vista, show_clusters = TRUE)
#> Too few points to calculate an ellipse
#> Too few points to calculate an ellipse
#> Warning: Removed 2 rows containing missing values or values outside the scale range
#> (`geom_path()`).