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fit_SE for combination screens

Source: R/fit_SE.combinations.R
fit_SE.combinations.Rd

Perform fittings for combination screens.

Usage

fit_SE.combinations(
  se,
  data_type = gDRutils::get_supported_experiments("combo"),
  series_identifiers = NULL,
  normalization_types = c("GR", "RV"),
  averaged_assay = "Averaged",
  metrics_assay = "Metrics",
  score_FUN = calculate_score
)

Arguments

se

SummarizedExperiment object with a BumpyMatrix assay containing averaged data.

data_type

single-agent vs combination

series_identifiers

character vector of the column names in the nested DFrame corresponding to nested identifiers.

normalization_types

character vector of normalization types used for calculating combo matrix.

averaged_assay

string of the name of the averaged assay to use as input. in the se.

metrics_assay

string of the name of the metrics assay to output in the returned SummarizedExperiment. whose combination represents a unique series for which to fit curves.

score_FUN

function used to calculate score for HSA and Bliss

Value

A SummarizedExperiment object with an additional assay containing the combination metrics.

Details

This function assumes that the combination is set up with both concentrations nested in the assay.

Examples

fmae_cms <- gDRutils::get_synthetic_data("finalMAE_combo_matrix_small")

se1 <- fmae_cms[[gDRutils::get_supported_experiments("combo")]]
SummarizedExperiment::assays(se1) <-
  SummarizedExperiment::assays(se1)["Averaged"]
fit_SE.combinations(se1[1, 1])
#> Warning: overriding original x_0 argument '1' with '1' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '1' with '1' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '0.93772095952509' with '0.9563' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '0.411661143403877' with '0.4075' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '-0.466087101282731' with '-0.4678' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '-0.638711813666124' with '-0.5972' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '-0.652503025819777' with '-0.6296' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '-0.653485583859241' with '-0.692' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '-0.653555270839699' with '-0.7039' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '-0.65356019156576' with '-0.7046' (only 1 normalized value detected, setting constant fit)
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: overriding original x_0 argument '1' with '1' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '1' with '1' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '0.960100165903774' with '0.966' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '0.578859775899097' with '0.577' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '0.123503648078603' with '0.1259' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '0.0689925257550913' with '0.0814' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '0.0658336504167374' with '0.0714' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '0.0656619818287096' with '0.0535' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '0.065652646099779' with '0.0503' (only 1 normalized value detected, setting constant fit)
#> Warning: overriding original x_0 argument '0.0656521405542169' with '0.0501' (only 1 normalized value detected, setting constant fit)
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> class: SummarizedExperiment 
#> dim: 1 1 
#> metadata(3): identifiers experiment_metadata Keys
#> assays(6): Averaged Metrics ... all_iso_points scores
#> rownames(1): G00004_drug_004_moa_A_G00021_drug_021_moa_D_72
#> rowData names(7): Gnumber DrugName ... drug_moa_2 Duration
#> colnames(1): CL00016_cellline_GB_tissue_y_46
#> colData names(4): clid CellLineName Tissue ReferenceDivisionTime