drugSensitivitySig: get drug sensitivity values

In bhklab/Xeva: Analysis of patient-derived xenograft (PDX) data

get drug sensitivity values

Description

Given a Xeva object and drug name, this function will return sensitivity values for all the genes/features.

Usage

drugSensitivitySig(
  object,
  drug,
  mDataType = NULL,
  molData = NULL,
  features = NULL,
  model.ids = NULL,
  model2bidMap = NULL,
  sensitivity.measure = "slope",
  fit = c("lm", "CI", "pearson", "spearman", NA),
  standardize = c("SD", "rescale", "none"),
  nthread = 1,
  tissue = NULL,
  verbose = TRUE
)

Arguments

object	The Xeva dataset.
drug	Name of the drug.
mDataType	Molecular data type.
molData	External data matrix. Rows as features and columns as samples.
features	Set which molecular data features to use. Default NULL will use all features.
model.ids	Set which model.id to use from the dataset. Default NULL will use all model.ids.
model2bidMap	A data.frame with model.id and biobase.id. Default NULL will use internal mapping.
sensitivity.measure	Name of the sensitivity measure.
fit	Association method to use, can be 'lm', 'CI', 'pearson' or 'spearman'. If 'NA' only the data will be return. Default lm.
standardize	Default SD. Name of the method to use for data standardization before fitting.
nthread	number of threads
tissue	tissue type. Default NULL uses 'tissue' from object.
verbose	Default TRUE will show information

Details

Method to compute association can be specified by fit. It can be one of the:

• "lm" for linear models

• "CI" for concordance index

• "pearson" for Pearson correlation

• "spearman" for Spearman correlation

If fit is set to NA, processed data (an ExpressionSet) will be returned.

A matrix of values can be directly passed to molData. In case where a model.id maps to multiple biobase.ids, the first biobase.id in the data.frame will be used.

Value

A data.frame with features and values.

Examples

data(brca)
senSig <- drugSensitivitySig(object=brca, drug="tamoxifen",
                             mDataType="RNASeq", features=c(1,2,3,4,5),
                             sensitivity.measure="slope", fit = "lm")

## example to compute the Pearson correlation between gene expression and PDX response
senSig <- drugSensitivitySig(object=brca, drug="tamoxifen",
                             mDataType="RNASeq", features=c(1,2,3,4,5),
                             sensitivity.measure="slope", fit = "pearson")

bhklab/Xeva documentation built on Nov. 30, 2024, 3:17 a.m.