View source: R/tidyMS_aggregation.R
plot_hierarchies_line | R Documentation |
Plot peptide intensities of protein as a function of the sample and factor
plot_hierarchies_line(
res,
proteinName,
config,
separate = FALSE,
show.legend = FALSE
)
res |
data.frame |
proteinName |
title of plot |
config |
AnalysisConfiguration |
separate |
if heavy and light show in one plot or with separate y axis? |
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_estimate()
,
plot_hierarchies_add_quantline()
,
plot_hierarchies_line_df()
,
rlm_estimate()
,
rlm_estimate_dfconfig()
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_hierarchies_add_quantline()
,
plot_hierarchies_boxplot_df()
,
plot_hierarchies_line_df()
,
plot_intensity_distribution_violin()
,
plot_pca()
,
plot_raster()
,
plot_sample_correlation()
,
plot_screeplot()
istar <- sim_lfq_data_peptide_config()
config <- istar$config
analysis <- istar$data
xnested <- analysis |>
dplyr::group_by_at(config$table$hierarchy_keys_depth()) |> tidyr::nest()
prolfqua::plot_hierarchies_line(xnested$data[[1]], xnested$protein_Id[[1]],config )
bb <- prolfqua_data('data_skylineSRM_HL_A')
conf <- bb$config_f()
analysis <- bb$analysis(bb$data, conf)
nest <- analysis |> dplyr::group_by(conf$table$hierarchy_keys_depth()) |> tidyr::nest()
prolfqua::plot_hierarchies_line(nest$data[[1]],
"DUM",
conf,
separate = TRUE)
prolfqua::plot_hierarchies_line(nest$data[[1]],
"DUM",
conf,
separate = TRUE,
show.legend = TRUE)
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