Plot drug response curves for single-agent data for selected call lines and drugs
Source:R/plot-sa-response_curve.R
plot_dose_response_sa_by_drugs.RdPlot drug response curves for single-agent data for selected call lines and drugs
Usage
plot_dose_response_sa_by_drugs(
dt_metrics,
dt_average,
cellline_name_vec = NULL,
drug_name_vec = NULL,
normalization_type = "GR",
colors_vec = NULL,
plot_averaged_flag = TRUE,
plot_fit_flag = TRUE,
fit_source = "gDR"
)Arguments
- dt_metrics
data.table representing data from the
Metricsassay, outputted bygDRutils::convert_se_assay_to_dt(se, "Metrics")and single-agentSummarizedExperiment- dt_average
data.table representing data from the
Averagedassay, outputted bygDRutils::convert_se_assay_to_dt(se, "Averaged")and single-agentSummarizedExperiment- cellline_name_vec
character vector with cell line names to be plotted (Cell Line Name)
- drug_name_vec
character vector with drug names to be plotted (Drug Name)
- normalization_type
string with normalization_types to be selected one of: "GR" ("GRvalue") or "RV" ("RelativeViability")
- colors_vec
character vector with colors for
group_names- name or hex value- plot_averaged_flag
logical flag whether plot points with average values
- plot_fit_flag
logical flag whether plot points with fitted values
- fit_source
string source name for metrics
Examples
mae <- gDRutils::get_synthetic_data("small")
se <- mae[[gDRutils::get_supported_experiments("sa")]]
dt_metrics <- gDRutils::convert_se_assay_to_dt(se, "Metrics")
dt_average <- gDRutils::convert_se_assay_to_dt(se, "Averaged")
cellline_name_vec <- unique(dt_metrics[["CellLineName"]])[2:5]
drug_name_vec <- unique(dt_metrics[["DrugName"]])[5:7]
plot_dose_response_sa_by_drugs(dt_metrics = dt_metrics,
dt_average = dt_average,
cellline_name_vec = cellline_name_vec,
drug_name_vec = drug_name_vec,
normalization_type = "RV",
colors_vec = c("#00008B", "#FF6347", "#4CBB17"))
#> $cellline_CA
#>
#> $cellline_DA
#>
#> $cellline_EA
#>
#> $cellline_FA
#>