dataExtractor: dataExtractor: extract data from a CancerPanel object

In gmelloni/PrecisionTrialDesigner: A Tool to Analyze and Design NGS Based Custom Gene Panels

dataExtractor: extract data from a CancerPanel object

Description

Given user specified options, return specific data from a CancerPanel object, including alteration and Samples

Usage

dataExtractor(object 
    , alterationType=c("copynumber" , "expression" , "mutations" , "fusions")
    , tumor_type=NULL 
    , collapseMutationByGene=TRUE 
    , collapseByGene=FALSE 
    , tumor.weights=NULL)

Arguments

object	An instance of class CancerPanel
alterationType	what kind of alteration to include. It can be one or more between "copynumber", "expression", "mutations", "fusions". Default is to include all kind of alterations.
tumor_type	only plot one or more tumor types among the ones available in the object.
collapseMutationByGene	A logical that collapse all mutations on the same gene for a single patient as a single alteration.
collapseByGene	A logical that collapse all alterations on the same gene for a single patient as a single alteration. e.g. if a sample has TP53 both mutated and deleted as copynumber, it will count for one alteration only.
tumor.weights	A named vector of integer values containing an amount of samples to be randomly sampled from the data. Each element should correspond to a different tumor type and is named after its tumor code. See details

Details

This function is used internally by most of the methods of the package and provide a common data extractor for a CancerPanel object. It is a low level function to retrieve data for other custom usages, in particular via tumor.weights.

Value

A named list with data, samples and tumors not present in the CancerPanel object is returned.

Author(s)

Giorgio Melloni , Alessandro Guida

See Also

getAlterations subsetAlterations

Examples

# Retrieve example data
data(cpObj)
# Extract CNA and mutation data
mydata <- dataExtractor(cpObj 
, alterationType=c("copynumber" , "mutations") 
, tumor_type="brca")
# It is particularly useful for bootstrap simulations
# Here we extract 10 random samples composed by 30 brca and 40 luad
myboot <- replicate(10
, dataExtractor(cpObj
, alterationType="mutations"
, tumor.weights=c("brca"=30 , "luad"=40)
))

gmelloni/PrecisionTrialDesigner documentation built on March 3, 2023, 6:10 a.m.