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visualize intensity distributions

Source: R/tidyMS_plotting.R
plot_intensity_distribution_violin.Rd

visualize intensity distributions

visualize intensity distributions

Usage

plot_intensity_distribution_violin(
  pdata,
  sample_name,
  response,
  is_transformed = FALSE
)

plot_intensity_distribution_density(
  pdata,
  sample_name,
  response,
  is_transformed = FALSE,
  legend = TRUE
)

Arguments

pdata

data.frame

sample_name

character — sample column name

response

character — intensity column name

is_transformed

logical — is intensity log-transformed?

legend

do not show legend

See also

Other plotting: ContrastsPlotter, INTERNAL_FUNCTIONS_BY_FAMILY, medpolish_estimate_df(), missigness_histogram(), missingness_per_condition(), missingness_per_condition_cumsum(), plot_estimate(), plot_heatmap(), plot_heatmap_cor(), plot_hierarchies_add_quantline(), plot_hierarchies_boxplot_df(), plot_hierarchies_line(), plot_hierarchies_line_df(), plot_na_heatmap(), plot_pca(), plot_raster(), plot_sample_correlation(), upset_interaction_missing_stats(), upset_missing_stats()

Other plotting: ContrastsPlotter, INTERNAL_FUNCTIONS_BY_FAMILY, medpolish_estimate_df(), missigness_histogram(), missingness_per_condition(), missingness_per_condition_cumsum(), plot_estimate(), plot_heatmap(), plot_heatmap_cor(), plot_hierarchies_add_quantline(), plot_hierarchies_boxplot_df(), plot_hierarchies_line(), plot_hierarchies_line_df(), plot_na_heatmap(), plot_pca(), plot_raster(), plot_sample_correlation(), upset_interaction_missing_stats(), upset_missing_stats()

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$config)
plot_intensity_distribution_violin(
  lfq$get_data(), lfq$sample_name(), lfq$response(), lfq$is_transformed())
#> Warning: Removed 36 rows containing non-finite outside the scale range
#> (`stat_ydensity()`).
#> Warning: Removed 36 rows containing non-finite outside the scale range
#> (`stat_summary()`).


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$config)
plot_intensity_distribution_density(
  lfq$get_data(), lfq$sample_name(), lfq$response(), lfq$is_transformed())
#> Warning: Removed 36 rows containing non-finite outside the scale range
#> (`stat_density()`).