View source: R/tidyMS_aggregation.R
plot_estimate | R Documentation |
Plot feature data and result of aggregation
plot_estimate(data, config, data_aggr, config_reduced, show.legend = FALSE)
data |
data.frame before aggregation |
config |
AnalyisConfiguration |
data_aggr |
data.frame after aggregation |
config_aggr |
AnalysisConfiguration of aggregated data |
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_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 aggregation:
INTERNAL_FUNCTIONS_BY_FAMILY
,
aggregate_intensity_topN()
,
estimate_intensity()
,
intensity_summary_by_hkeys()
,
medpolish_estimate()
,
medpolish_estimate_df()
,
medpolish_estimate_dfconfig()
,
medpolish_protein_estimates()
,
plot_hierarchies_add_quantline()
,
plot_hierarchies_line()
,
plot_hierarchies_line_df()
,
rlm_estimate()
,
rlm_estimate_dfconfig()
istar <- sim_lfq_data_peptide_config()
config <- istar$config
analysis <- istar$data
analysis <- prolfqua::transform_work_intensity(analysis, config, log2)
bbMed <- estimate_intensity(analysis, config, .func = medpolish_estimate_dfconfig)
tmpMed <- plot_estimate(analysis, config, bbMed$data, bbMed$config)
stopifnot("ggplot" %in% class(tmpMed$plots[[1]]))
stopifnot("ggplot" %in% class(tmpMed$plots[[2]]))
bbRob <- estimate_intensity(analysis, config, .func = rlm_estimate_dfconfig)
tmpRob <- plot_estimate(analysis, config, bbRob$data, bbRob$config)
stopifnot("ggplot" %in% class(tmpRob$plots[[1]]))
stopifnot("ggplot" %in% class(tmpRob$plots[[2]]))
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