Plot panel with boxplots
Usage
plot_boxplot_num_panel(
dt_response,
dt_depmap,
selected_feats,
selected_feat_meta_col = NULL,
ncol = NULL
)Arguments
- dt_response
data.tablewith 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_scoresorprep_dt_response_metric_diff,- dt_depmap
data.tablewith dependent variables data loaded from DepMap - for one feature; (rows are samples, columns are features). outputted byprep_dt_depmap_feat- selected_feats
character vector with names of selected features 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)
- ncol
number of plot column in panel
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_panel(
dt_response = dt_response,
dt_depmap = obj_depmap_meta[["dt_depmap"]],
selected_feats = names(obj_depmap_meta[["dt_depmap"]])[3:5])