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Plot peptide intensities of protein as a function of the sample and factor

Source: R/tidyMS_aggregation.R
plot_hierarchies_line.Rd

Plot peptide intensities of protein as a function of the sample and factor

Usage

plot_hierarchies_line(
  res,
  proteinName,
  config,
  separate = FALSE,
  show.legend = FALSE
)

Arguments

res

data.frame

proteinName

title of plot

config

AnalysisConfiguration

separate

if heavy and light show in one plot or with separate y axis?

See also

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_heatmap_cor_iheatmap(), 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()

Examples



istar <- sim_lfq_data_peptide_config()
#> creating sampleName from fileName column
#> completing cases
#> completing cases done
#> setup done
config <- istar$config
analysis <- istar$data

xnested <- analysis |>
  dplyr::group_by(across(all_of(config$hierarchy_keys_depth()))) |>
  tidyr::nest()

prolfqua::plot_hierarchies_line(xnested$data[[1]], xnested$protein_Id[[1]], config)
#> Warning: Removed 7 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 4 rows containing missing values or values outside the scale range
#> (`geom_line()`).


bb <- prolfqua_data("data_skylineSRM_HL_A")
conf <- bb$config_f()
analysis <- bb$analysis(bb$data, conf)
#> creating sampleName from fileName column
#> Warning: no nr_children column specified in the data, adding column nr_children and setting to 1.
#> completing cases
#> completing cases done
#> setup done

nest <- analysis |>
  dplyr::group_by(conf$hierarchy_keys_depth()) |>
  tidyr::nest()
prolfqua::plot_hierarchies_line(nest$data[[1]],
  "DUM",
  conf,
  separate = TRUE
)
#> Warning: Removed 802 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 750 rows containing missing values or values outside the scale range
#> (`geom_line()`).

prolfqua::plot_hierarchies_line(nest$data[[1]],
  "DUM",
  conf,
  separate = TRUE,
  show.legend = TRUE
)
#> Warning: Removed 802 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 750 rows containing missing values or values outside the scale range
#> (`geom_line()`).