generates peptide level plots for all Proteins
Source:R/tidyMS_plotting.R
plot_hierarchies_boxplot_df.Rdgenerates peptide level plots for all Proteins
Usage
plot_hierarchies_boxplot_df(
pdata,
lfqdata,
hierarchy = lfqdata$relevant_hierarchy_keys(),
facet_grid_on = NULL
)See also
Other plotting:
ContrastsPlotter,
INTERNAL_FUNCTIONS_BY_FAMILY,
medpolish_estimate_df(),
missigness_histogram(),
missingness_per_condition(),
missingness_per_condition_cumsum(),
plot_estimate(),
plot_heatmap(),
plot_heatmap_cor(),
plot_hierarchies_add_quantline(),
plot_hierarchies_line(),
plot_hierarchies_line_df(),
plot_intensity_distribution_violin(),
plot_na_heatmap(),
plot_pca(),
plot_raster(),
plot_sample_correlation(),
upset_interaction_missing_stats(),
upset_missing_stats()
Examples
istar <- sim_lfq_data_peptide_config()
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
lfq <- LFQData$new(istar$data, istar$config)
res <- plot_hierarchies_boxplot_df(lfq$data_long(), lfq)
res$boxplot[[1]]
#> Warning: Removed 7 rows containing non-finite outside the scale range
#> (`stat_boxplot()`).
#> Warning: Removed 7 rows containing non-finite outside the scale range
#> (`stat_summary()`).
#> Warning: Removed 7 rows containing non-finite outside the scale range
#> (`stat_summary()`).
#> Warning: Removed 7 rows containing missing values or values outside the scale range
#> (`position_quasirandom()`).
lfq2 <- LFQData$new(
istar$data |> dplyr::filter(protein_Id %in% sample(protein_Id, 2)),
istar$config)
res <- plot_hierarchies_boxplot_df(lfq2$data_long(), lfq2)
res$boxplot[[1]]
#> Warning: Removed 8 rows containing non-finite outside the scale range
#> (`stat_boxplot()`).
#> Warning: Removed 8 rows containing non-finite outside the scale range
#> (`stat_summary()`).
#> Warning: Removed 8 rows containing non-finite outside the scale range
#> (`stat_summary()`).
#> Warning: Removed 8 rows containing missing values or values outside the scale range
#> (`position_quasirandom()`).