drugSensitivitySig: get drug sensitivity values

Description Usage Arguments Details Value Examples

View source: R/drug_Sensitivity_Signature.R

Description

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

Usage

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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:

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

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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")

Xeva documentation built on Nov. 8, 2020, 5:56 p.m.