plot_pca: plot PCA

In wolski/prolfqua: Proteomics Label Free Quantification

plot PCA

Description

plot PCA

Usage

plot_pca(
  data,
  config,
  PC = c(1, 2),
  add_txt = FALSE,
  plotly = FALSE,
  impute = TRUE,
  nudge = 0.1
)

See Also

Other plotting: ContrastsPlotter, INTERNAL_FUNCTIONS_BY_FAMILY, UpSet_interaction_missing_stats(), UpSet_missing_stats(), medpolish_estimate_df(), missigness_histogram(), missingness_per_condition(), missingness_per_condition_cumsum(), plot_NA_heatmap(), plot_estimate(), plot_heatmap(), plot_heatmap_cor(), plot_heatmap_cor_iheatmap(), plot_hierarchies_add_quantline(), plot_hierarchies_boxplot_df(), plot_hierarchies_line(), plot_hierarchies_line_df(), plot_intensity_distribution_violin(), plot_raster(), plot_sample_correlation(), plot_screeplot()

Examples

istar <- sim_lfq_data_protein_config(with_missing = TRUE, weight_missing = .8, Nprot = 3000)
config <- istar$config
analysis <- istar$data
tmp <- plot_pca(analysis, config, add_txt= TRUE, impute = FALSE)
print(tmp)
tmp <- plot_pca(analysis, config, add_txt= TRUE, impute=TRUE, nudge = 0.01)
print(tmp)

stopifnot("ggplot" %in% class(tmp) )
tmp <- plot_pca(analysis, config, add_txt= FALSE)
stopifnot("ggplot" %in% class(tmp) )
#tmp
tmp <- plot_pca(analysis, config, PC = c(1,2))
stopifnot("ggplot" %in% class(tmp) )
tmp <- plot_pca(analysis, config, PC = c(2,40))
print(tmp)
#stopifnot(is.null(tmp))

wolski/prolfqua documentation built on June 8, 2025, 5:19 a.m.