drugSensitivitySig {PharmacoGx} | R Documentation

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

### Description

Given a Pharmacoset 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.

### Usage

    drugSensitivitySig(pSet, mDataType, drugs, features, cells, tissues,
      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"), molecular.cutoff = NA,
      molecular.cutoff.direction = c("less", "greater"), nthread = 1,
      verbose = TRUE, ...)

### Arguments

`pSet` | [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
`drugs` | [character] a vector of drug names 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.
`cells` | [character] allows choosing exactly which cell lines to include for the signature fitting. Should be a subset of cellNames(pSet)
`tissues` | [character] a vector of which tissue types to include in the signature fitting. Should be a subset of cellInfo(pSet)$tissueid
`sensitivity.measure` | [character] which measure of the drug dose 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 drug pair?
`sensitivity.cutoff` | [numeric] Allows the user to binarize the sensitivity data using this threshold.
`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.
`molecular.cutoff` | Allows the user to binarize the sensitivity data using this threshold.
`molecular.cutoff.direction` | [character] One of "less" or "greater", allows to set direction of binarization.
`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, drugs in the second, and return values in the third.

### Examples

    data(GDSCsmall)
    drug.sensitivity <- drugSensitivitySig(GDSCsmall, mDataType="rna",
                 nthread=1, features = fNames(GDSCsmall, "rna")[1])
    print(drug.sensitivity)

[Package PharmacoGx version 1.12.0 Index]