Create a nested list of plots for PRISM data with single-agent metrics

Usage

create_PRISM_plot_list_sa(
  drug_name_vec,
  dt_metrics,
  dt_average = NULL,
  normalization_type_vec = "RV",
  metric = c("xc50", "x_mean", "x_max"),
  fit_source = "gDR",
  meta_data_path,
  feat_data_path,
  feature_sets,
  metadata_columns = NULL,
  clear_taxonomy_info = TRUE,
  with_decoding = FALSE
)

Arguments

drug_name_vec: character vector with drug names to be plotted (identifiers DrugName)
dt_metrics: data.table representing data from the Metrics assay, outputted by gDRutils::convert_se_assay_to_dt(se, "Metrics") and single-agent SummarizedExperiment
dt_average: data.table representing data from the Averaged assay, outputted by gDRutils::convert_se_assay_to_dt(se, "Averaged") and single-agent SummarizedExperiment
normalization_type_vec: character vector with normalization types to be selected one of: "GR" ("GRvalue") or "RV" ("RelativeViability") or both
metric: character vector with names of metric; chosen from: "xc50" ("GR50" or "IC50" - respectively depending on normalization_type), "x_max" ("GR Max" or "E Max") or "x_mean" ("GR Mean" or "RV Mean")
fit_source: string source name for metrics
meta_data_path: string path to metadata file describing all cancer models/cell lines which are referenced by a dataset contained within the DepMap portal. It is usually a file named Model.csv or Model.csv.gz.
feat_data_path: string path to the directory containing the molecular feature set file to load from DepMap.
feature_sets: character vector containing the names of the molecular feature sets to load from DepMap. These names should also correspond to the file names containing the feature data (without the extension, which is assumed to be csv or csv.gz)
metadata_columns: character vector with the metadata columns to load for DepMap cell lines
clear_taxonomy_info: logical flag whether to remove taxonomy information for gene names in table with the molecular feature sets from DepMap.
with_decoding: logical whether the feature OmicsArmLevelCNA, OmicsSomaticMutationsMatrixHotspot and OmicsSomaticMutationsMatrixDamaging should be encoded into a 0-1 scheme

Value

A named list with elements:

ls_plot nested list of plots for selected type of experiment
ls_assoc_data nested list of table with association data

Author

Janina Smoła janina.smola@external.roche.com

Examples

mae <- qs2::qs_read(system.file("testdata/finalMAE_prism.qs2", package = "gDRtestData"))
se <- mae[[gDRutils::get_supported_experiments("sa")]]
dt_metrics <- gDRutils::convert_se_assay_to_dt(se, "Metrics")
drug_name <- unique(dt_metrics[[gDRutils::get_env_identifiers("drug_name")]])[1]
create_PRISM_plot_list_sa(
  drug_name_vec = drug_name,
  dt_metrics = dt_metrics,
  meta_data_path = system.file("depmap_data/Model.csv.gz", package = "gDRtestData"),
  feat_data_path = system.file("depmap_data", package = "gDRtestData"),
  feature_sets = c("CRISPRGeneEffect")
)
#> $ls_plot
#> $ls_plot$CRISPRGeneEffect
#> $ls_plot$CRISPRGeneEffect$`GDC-8025`
#> $ls_plot$CRISPRGeneEffect$`GDC-8025`$RV
#> $ls_plot$CRISPRGeneEffect$`GDC-8025`$RV$RV_gDR_log10_xc50

#> 
#> $ls_plot$CRISPRGeneEffect$`GDC-8025`$RV$RV_gDR_x_mean

#> 
#> $ls_plot$CRISPRGeneEffect$`GDC-8025`$RV$RV_gDR_x_max

#> 
#> 
#> 
#> 
#> 
#> $ls_assoc_data
#> $ls_assoc_data$CRISPRGeneEffect
#> $ls_assoc_data$CRISPRGeneEffect$`GDC-8025`
#> $ls_assoc_data$CRISPRGeneEffect$`GDC-8025`$RV
#> $ls_assoc_data$CRISPRGeneEffect$`GDC-8025`$RV$RV_gDR_log10_xc50
#>      feature          response         rho     q_value neglog_q_value
#>       <char>            <char>       <num>       <num>          <num>
#>   1:   FGFR1 RV_gDR_log10_xc50  0.33979097 0.003069564     2.51292337
#>   2:   FOXP1 RV_gDR_log10_xc50  0.15165775 0.443164057     0.35343547
#>   3:    BCL2 RV_gDR_log10_xc50  0.14298724 0.591219704     0.22825110
#>   4:    TP53 RV_gDR_log10_xc50 -0.19118940 0.666613242     0.17612606
#>   5:    DSC3 RV_gDR_log10_xc50  0.14608629 0.713441788     0.14664146
#>  ---                                                                 
#> 145:   SF3B1 RV_gDR_log10_xc50 -0.02123908 0.946104103     0.02406107
#> 146:   KMT2D RV_gDR_log10_xc50 -0.01340607 0.946324813     0.02395977
#> 147:   U2AF1 RV_gDR_log10_xc50 -0.02160233 0.946546062     0.02385825
#> 148:    RHOA RV_gDR_log10_xc50 -0.02909737 0.946773401     0.02375395
#> 149:    CDK4 RV_gDR_log10_xc50 -0.06813350 0.947026529     0.02363785
#> 
#> $ls_assoc_data$CRISPRGeneEffect$`GDC-8025`$RV$RV_gDR_x_mean
#>      feature      response          rho      q_value neglog_q_value
#>       <char>        <char>        <num>        <num>          <num>
#>   1:   FGFR1 RV_gDR_x_mean  0.293106529 2.913225e-11    10.53562599
#>   2:    TP53 RV_gDR_x_mean -0.148226553 9.231880e-03     2.03470986
#>   3:    JAK2 RV_gDR_x_mean  0.113757797 1.985975e-01     0.70202617
#>   4:     CIC RV_gDR_x_mean -0.087622859 3.114935e-01     0.50655098
#>   5:    CDK4 RV_gDR_x_mean -0.077563596 3.854880e-01     0.41398915
#>  ---                                                               
#> 145:  RICTOR RV_gDR_x_mean  0.023985942 8.653591e-01     0.06280365
#> 146:   U2AF1 RV_gDR_x_mean  0.007235126 8.659303e-01     0.06251708
#> 147:  NFE2L2 RV_gDR_x_mean  0.024250178 8.665097e-01     0.06222657
#> 148:    RHOA RV_gDR_x_mean  0.006994082 8.671018e-01     0.06192993
#> 149:   KMT2D RV_gDR_x_mean  0.037048856 8.677244e-01     0.06161818
#> 
#> $ls_assoc_data$CRISPRGeneEffect$`GDC-8025`$RV$RV_gDR_x_max
#>      feature     response          rho      q_value neglog_q_value
#>       <char>       <char>        <num>        <num>          <num>
#>   1:   FGFR1 RV_gDR_x_max  0.195605854 0.0001257931      3.9003433
#>   2:    RAF1 RV_gDR_x_max -0.124550350 0.0477535114      1.3209947
#>   3:    CDK4 RV_gDR_x_max -0.113555600 0.0728986016      1.1372808
#>   4:    RXRA RV_gDR_x_max  0.120542996 0.0971801709      1.0124223
#>   5:    CHD4 RV_gDR_x_max -0.101488117 0.1247265632      0.9040410
#>  ---                                                              
#> 145:   U2AF1 RV_gDR_x_max -0.010956099 0.7162334723      0.1449454
#> 146:   H3-3A RV_gDR_x_max -0.004571759 0.7172936121      0.1443030
#> 147:    POT1 RV_gDR_x_max  0.010742777 0.7183433953      0.1436679
#> 148:    RHOA RV_gDR_x_max  0.042633228 0.7194681062      0.1429885
#> 149:    TSC2 RV_gDR_x_max -0.010164816 0.7206948251      0.1422486
#> 
#> 
#> 
#> 
#>