radSensitivitySig: Creates a signature representing the association between gene...
In RadioGx: Analysis of Large-Scale Radio-Genomic Data

Description Usage Arguments Value Examples

Given a RadioSet of the sensitivity experiment type, and a list of drugs, the function will compute a signature for the effect 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.

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, standardize = c("SD", "rescale", "none"),
  nthread = 1, verbose = TRUE, ...)

`rSet`	[PharmacoSet] a PharmacoSet 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

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

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