Class "CNSet"

Description

CNSet is a container for intermediate data and parameters pertaining to allele-specific copy number estimation. Methods for CNSet objects, including accessors for linear model parameters and allele-specific copy number are included here.

Objects from the Class

An object from the class is not generally intended to be initialized by the user, but returned by the genotype function in the crlmm package.

The following creates a very basic CNSet with assayData containing the required elements.

new(CNSet, alleleA=new("matrix"), alleleB=new("matrix"), call=new("matrix"), callProbability=new("matrix"), batch=new("factor"))

Slots

batch:

Object of class "factor" ~~

batchStatistics:

Object of class "AssayData" ~~

assayData:

Object of class "AssayData" ~~

phenoData:

Object of class "AnnotatedDataFrame" ~~

featureData:

Object of class "AnnotatedDataFrame" ~~

experimentData:

Object of class "MIAME" ~~

annotation:

Object of class "character" ~~

protocolData:

Object of class "AnnotatedDataFrame" ~~

datadir:

Object of class "list"~~

mixtureParams:

Object of class "matrix"~~

.__classVersion__:

Object of class "Versions" ~~

Methods

The argument object for the following methods is a CNSet.

object[i, j]: subset the CNSet object by markers (i) and/or samples (j).

A(objet): accessor for the normalized intensities of allele A

A(object) <- value: replace intensities for the A allele intensities by value. The object value must be a matrix, ff_matrix, or ffdf.

allele(object, allele): accessor for the normalized intensities for the A or B allele. The argument for allele must be either 'A' or 'B'

B(objet): accessor for the normalized intensities of allele B

B(object) <- value: replace intensities for the B allele intensities by value. The object value must be a matrix, ff_matrix, or ffdf.

batch(object): vector of batch labels for each sample.

batchNames(object): the unique batch names

batchNames(object) <- value: relabel the batches

calls(object): accessor for genotype calls coded as 1 (AA), 2 (AB), or 3 (BB). Nonpolymorphic markers are NA.

confs(object): accessor for the genotype confidence scores.

close(object): close any open file connections to ff objects stored in the CNSet object.

as(object, "oligoSnpSet"): coerce a CNSet object to an object of class oligoSnpSet – a container for the total copy number and genotype calls.

corr(object): the correlation of the A and B intensities within each genotype.

flags(object): flags to indicate possible problems with the copy number estimation. Not fully implemented at this point.

new("CNSet"): instantiating a CNSet object.

nu(object, allele): accessor for the intercept (background) for the A and B alleles. The value of allele must be 'A' or 'B'.

open(object) open file connections for all ff objects stored in the CNSet object.

nu(object, allele): accessor for the slope for the A and B alleles. The value of allele must be 'A' or 'B'.

sigma2(object, allele): accessor for the within genotype variance

tau2(object, allele): accessor for background variance

Author(s)

R. Scharpf

Examples

	new("CNSet")

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(oligoClasses)
Welcome to oligoClasses version 1.34.0
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/oligoClasses/CNSet-class.Rd_%03d_medium.png", width=480, height=480)
> ### Name: CNSet-class
> ### Title: Class "CNSet"
> ### Aliases: CNSet-class CNSet [,CNSet-method [,CNSet,ANY-method
> ###   A,CNSet-method A<-,CNSet-method allele,CNSet-method B,CNSet-method
> ###   B<-,CNSet-method batch,CNSet-method batchNames,CNSet-method
> ###   batchNames<-,CNSet-method batchStatistics,CNSet-method
> ###   batchStatistics<-,CNSet,AssayData-method calls,CNSet-method
> ###   calls<-,CNSet,matrix-method close,CNSet-method
> ###   coerce,CNSetLM,CNSet-method coerce,CNSet,CopyNumberSet-method
> ###   coerce,CNSet,oligoSnpSet coerce,CNSet,oligoSnpSet-method
> ###   confs,CNSet-method confs<-,CNSet,matrix-method
> ###   corr,CNSet,character-method flags,CNSet-method
> ###   initialize,CNSet-method initialize,CNSetLM-method
> ###   nu,CNSet,character-method open,CNSet-method
> ###   phi,CNSet,character-method show,CNSet-method
> ###   snpCallProbability,CNSet-method sigma2,CNSet,character-method
> ###   tau2,CNSet,character-method updateObject,CNSet-method
> ### Keywords: classes
> 
> ### ** Examples
> 
> 	new("CNSet")
CNSet (assayData/batchStatistics elements: matrix)
CNSet (storageMode: lockedEnvironment)
assayData: 0 features, 0 samples 
  element names: alleleA, alleleB, call, callProbability 
protocolData: none
phenoData: none
featureData
  featureNames:
  fvarLabels: isSnp position chromosome
  fvarMetadata: labelDescription
experimentData: use 'experimentData(object)'
Annotation:  
genome:   
batch:    : 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>