drugSensitivitySig,PharmacoSet-method {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
## S4 method for signature 'PharmacoSet'
drugSensitivitySig(
object,
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
object |
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 |
character What summary statistic should be used to
summarize duplicates for cell line molecular profile measurements?
|
sensitivity.summary.stat |
character 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 |
logical 'TRUE' if the warnings and other informative message shoud be displayed
|
... |
additional arguments not currently fully supported by the function
|
Value
array
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 2.6.0
Index]