summarizeSensitivityProfiles,RadioSet-method {RadioGx} | R Documentation

## Takes the sensitivity data from a RadioSet, and summarises them into a drug vs cell line table

### Description

This function creates a table with cell lines as rows and radiation types as columns, summarising the drug senstitivity data of a RadioSet into drug-cell line pairs

### Usage

    ## S4 method for signature 'RadioSet'
    summarizeSensitivityProfiles(
      object,
      sensitivity.measure = "AUC_recomputed",
      cell.lines,
      radiation.types,
      summary.stat = c("mean", "median", "first", "last", "max", "min"),
      fill.missing = TRUE,
      verbose = TRUE
    )

### Arguments

`object` | 'RadioSet' The RadioSet from which to extract the data
`sensitivity.measure` | 'character' which sensitivity sensitivity.measure to use? Use the sensitivityMeasures function to find out what measures are available for each PSet.
`cell.lines` | 'character' The cell lines to be summarized. If any cell lines has no data, it will be filled with missing values
`radiation.types` | 'character' The radiation types to be summarized. If any radiation type has no data, it will be filled with missing values
`summary.stat` | 'character' which summary method to use if there are repeated cell line-drug experiments? Choices are "mean", "median", "first", or "last"
`fill.missing` | 'logical(1)' should the missing cell lines not in the molecular data object be filled in with missing values?
`verbose` | Should the function print progress messages?

### Value

[matrix] A matrix with cell lines going down the rows, radiation types across the columns, with the selected sensitivity statistic for each pair.

### Examples

    data(clevelandSmall)
    GDSCauc <- summarizeSensitivityProfiles(clevelandSmall, sensitivity.measure='AUC_published')

[Package RadioGx version 1.2.0 Index]