missingness_per_condition_cumsum: cumulative sums of missing

In wolski/prolfqua: Proteomics Label Free Quantification

cumulative sums of missing

Description

cumulative sums of missing

Usage

missingness_per_condition_cumsum(
  x,
  config,
  factors = config$table$factor_keys_depth()
)

See Also

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

Other imputation: UpSet_interaction_missing_stats(), UpSet_missing_stats(), get_contrast(), missigness_histogram(), missingness_per_condition()

Examples

istar <- sim_lfq_data_peptide_config()
config <- istar$config
analysis <- istar$data

res <- missingness_per_condition_cumsum(analysis,config)
stopifnot("ggplot" %in% class(res$figure))
stopifnot(ncol(res$data) >= 6)

wolski/prolfqua documentation built on May 12, 2024, 10:16 p.m.