Plot boxplot for categorical features

Usage

plot_boxplot_num(
  dt_response,
  dt_depmap,
  selected_feat,
  selected_feat_meta_col = NULL
)

Arguments

dt_response: data.table with experimental response data (rows are samples) for one metric outputted by one of functions: prep_dt_response_metric_sa, prep_dt_response_dose_sa, prep_dt_response_scores or prep_dt_response_metric_diff,
dt_depmap: data.table with dependent variables data loaded from DepMap - for one feature; (rows are samples, columns are features). outputted by prep_dt_depmap_feat
selected_feat: string with name of selected feature from dt_depmap
selected_feat_meta_col: string with the name of a feature column in DepMap (will be used as a plot title) that has 0-1 values only (categorical character but without relation one-to-one for ids and feature)

Value

ggplot object containing boxplots for variable levels

Author

Janina Smoła janina.smola@external.roche.com

Examples

mae_prism <- gDRutils::get_synthetic_data("prism")
se_prism <- mae_prism[[gDRutils::get_supported_experiments("sa")]]
dt_metrics <- gDRutils::convert_se_assay_to_dt(se_prism, "Metrics")
dt_response <- prep_dt_response_metric_sa(
  dt_metrics = dt_metrics,
  d_name = unique(dt_metrics[["DrugName"]])[1],
  normalization_type = "RV", metric = "x_mean")
meta_data_path <- system.file("depmap_data/Model.csv.gz", package = "gDRtestData")
obj_depmap_meta <- prep_dt_depmap_meta(meta_data_path, metadata_col = "OncotreeLineage")
plot_boxplot_num(
  dt_response = dt_response,
  dt_depmap = obj_depmap_meta[["dt_depmap"]],
  selected_feat = names(obj_depmap_meta[["dt_depmap"]])[3])