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Plot feature data and result of aggregation

Source: R/tidyMS_aggregation.R
plot_estimate.Rd

Plot feature data and result of aggregation

Usage

plot_estimate(lfqdata, lfqdata_agg, show.legend = FALSE)

Arguments

lfqdata

LFQData object (original data)

lfqdata_agg

LFQData object (aggregated data)

show.legend

logical, show legend in plot

See also

Other plotting: ContrastsPlotter, INTERNAL_FUNCTIONS_BY_FAMILY, medpolish_estimate_df(), missigness_histogram(), missingness_per_condition(), missingness_per_condition_cumsum(), 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_na_heatmap(), plot_pca(), plot_raster(), plot_sample_correlation(), upset_interaction_missing_stats(), upset_missing_stats()

Other aggregation: INTERNAL_FUNCTIONS_BY_FAMILY, aggregate_intensity_top_n(), estimate_intensity(), medpolish_estimate(), medpolish_estimate_df(), medpolish_estimate_dfconfig(), plot_hierarchies_add_quantline(), plot_hierarchies_line(), plot_hierarchies_line_df(), rlm_estimate(), rlm_estimate_dfconfig()

Examples


istar <- sim_lfq_data_peptide_config()
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
lfq <- LFQData$new(istar$data, istar$config)
lfq <- lfq$get_Transformer()$log2()$lfq
#> Column added : log2_abundance
bbMed <- estimate_intensity(lfq, .func = medpolish_estimate_dfconfig)
#> starting aggregation
lfq_med <- LFQData$new(bbMed$data, bbMed$config)
tmpMed <- plot_estimate(lfq, lfq_med)
stopifnot("ggplot" %in% class(tmpMed$plots[[1]]))