Creates a signature representing gene expression (or other molecular profile) change induced by administrating a drug, for use in drug effect analysis.
Source:R/drugPerturbationSig.R
drugPerturbationSig.Rd
Given a Pharmacoset of the perturbation experiment type, and a list of drugs, the function will compute a signature for the effect of drug concentration on the molecular profile of a cell. The algorithm uses a regression model which corrects for experimental batch effects, cell specific differences, and duration of experiment to isolate the effect of the concentration of the drug applied. The function returns the estimated coefficient for concentration, 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
drugPerturbationSig(
pSet,
mDataType,
drugs,
cells,
features,
nthread = 1,
returnValues = c("estimate", "tstat", "pvalue", "fdr"),
verbose = FALSE
)
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.- cells
character
a vector of cell names to use in computing 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.- nthread
numeric
if multiple cores are available, how many cores should the computation be parallelized over?- returnValues
character
Which of estimate, t-stat, p-value and fdr should the function return for each gene drug pair?- verbose
logical(1)
Should diagnostive messages be printed? (default false)