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Build a List of PCA Plots for Multiple Subsets

Source: R/PCA_Highcharts_Final.R
pca_highchart_list.Rd

Automatically builds PCA plots for "all", "any" and/or specific comparisons. Similar to factoextra::fviz_pca_ind with ellipse options.

Usage

pca_highchart_list(
  pca_input,
  modes = c("all", "any"),
  alpha = 0.05,
  color_by = "Condition",
  group_order = NULL,
  palette = NULL,
  addEllipses = TRUE,
  ellipse_type = c("convex", "confidence"),
  ellipse_level = 0.95,
  ellipse_fill_opacity = 0.12,
  ellipse_line_width = 1,
  ellipse_npoints = 100,
  point_size = 5,
  show_labels = FALSE,
  label_size = 10,
  center = TRUE,
  scale. = TRUE,
  filter_samples_to_comparison = FALSE
)

Arguments

pca_input

Data frame in long format (see build_pca_scores for the structure)

modes

Vector of modes to generate: "all", "any", and/or comparison names (default: c("all", "any"))

alpha

Significance threshold for DEPs (default: 0.05)

color_by

Column used to colour the points (default: "Condition")

group_order

Order of the groups/conditions (optional)

palette

Named vector of colours, or NULL for an automatic palette

addEllipses

Show ellipses/hulls around the groups (default: TRUE)

ellipse_type

Ellipse type: "convex" or "confidence" (default: "convex")

ellipse_level

Confidence level for ellipse_type = "confidence" (default: 0.95)

ellipse_fill_opacity

Ellipse fill opacity (0-1, default: 0.12)

ellipse_line_width

Outline line width (default: 1)

ellipse_npoints

Number of points for the confidence ellipse (default: 100)

point_size

Point radius (default: 5)

show_labels

Show the point labels (SampleID) (default: FALSE)

label_size

Label font size in px (default: 10)

center

Center the data before PCA (default: TRUE)

scale.

Scale the data before PCA (default: TRUE)

filter_samples_to_comparison

For specific comparisons, restrict the samples to the conditions involved (default: FALSE)

Value

Named list of highchart objects

Examples

data(nadia_dia)
res <- process_proteomics(nadia_dia, verbose = FALSE)

# One PCA over all proteins and one over the significant ones
hc_pcas <- pca_highchart_list(
  res$PCA_Input,
  modes         = c("all", "any"),
  group_order   = c("A", "B", "D"),
  ellipse_type  = "confidence",
  ellipse_level = 0.95
)
names(hc_pcas)
#> [1] "all" "any"