radSensitivitySig {RadioGx} | R Documentation

## Creates a signature representing the association between gene expression (or other molecular profile) and radiation dose response, for use in radiation sensitivity analysis.

### Description

Given a RadioSet of the sensitivity experiment type, and a list of radiation types, the function will compute a signature for the effect of gene expression on the molecular profile of a cell. The function returns the estimated coefficient, the t-stat, the p-value and the false discovery rate associated with that coefficient, in a 3 dimensional array, with genes in the first direction, drugs in the second, and the selected return values in the third.

### Usage

    radSensitivitySig(
      rSet,
      mDataType,
      radiation.types,
      features,
      sensitivity.measure = "AUC_recomputed",
      molecular.summary.stat = c("mean", "median", "first", "last", "or", "and"),
      sensitivity.summary.stat = c("mean", "median", "first", "last"),
      returnValues = c("estimate", "pvalue", "fdr"),
      sensitivity.cutoff = NA,
      standardize = c("SD", "rescale", "none"),
      nthread = 1,
      verbose = TRUE,
      ...
    )

### Arguments

`rSet` | A `RadioSet` of the perturbation experiment type
`mDataType` | `character` which one of the molecular data types to use in the analysis, out of dna, rna, rnaseq, snp, cnv
`radiation.types` | `character` a vector of radiation.types for which to compute the signatures. Should match the names used in the PharmacoSet.
`features` | `character` a vector of features for which to compute the signatures. Should match the names used in correspondant molecular data in PharmacoSet.
`sensitivity.measure` | `character` which measure of the radiation sensitivity should the function use for its computations? Use the sensitivityMeasures function to find out what measures are available for each PSet.
`molecular.summary.stat` | What summary statistic should be used to summarize duplicates for cell line molecular profile measurements?
`sensitivity.summary.stat` | What summary statistic should be used to summarize duplicates for cell line sensitivity measurements?
`returnValues` | `character` Which of estimate, t-stat, p-value and fdr should the function return for each gene?
`sensitivity.cutoff` | Allows to provide upper and lower bounds to sensitivity measures in the cases where the values exceed physical values due to numerical or other errors.
`standardize` | `character` One of "SD", "rescale", or "none", for the form of standardization of the data to use. If "SD", the the data is scaled so that SD = 1. If rescale, then the data is scaled so that the 95 interquantile range lies in [0,1]. If none no rescaling is done.
`nthread` | `numeric` if multiple cores are available, how many cores should the computation be parallelized over?
`verbose` | `boolean` 'TRUE' if the warnings and other infomrative message shoud be displayed
`...` | additional arguments not currently fully supported by the function

### Value

`list` a 3D array with genes in the first dimension, radiation.types in the second, and return values in the third.

### Examples

    data(clevelandSmall)
    rad.sensitivity <- radSensitivitySig(clevelandSmall, mDataType="rna",
                 nthread=1, features = fNames(clevelandSmall, "rna")[1],
                 radiation.types=radiationTypes(clevelandSmall))
    print(rad.sensitivity)

[Package RadioGx version 1.2.0 Index]