SnpSetIllumina {beadarraySNP} | R Documentation

## Class to Contain Objects Describing High-Throughput SNP Assays.

### Description

Container for high-throughput assays and experimental metadata. `SnpSetIllumina` class is derived from `eSet`, and requires matrices `R`, `G`, `call`, `callProbability` as assay data members.

It supports featureData. Several visualization methods use columns `CHR` and `MapInfo`. The `CHR` column is used to handle sex chromosomes in a specific way. The `OPA` column is the default way to specify subsamples.

### Extends

Directly extends class `eSet`.

### Creating Objects

`new('SnpSetIllumina', phenoData = [AnnotatedDataFrame], experimentData = [MIAME], annotation = [character], call = [matrix], callProbability = [matrix], G = [matrix], R = [matrix], featureData = [data.frameOrNULL], ...)`

`SnpSetIllumina` instances are usually created through `new("SnpSetIllumina", ...)`. Arguments to `new` include `call` (a matrix of gentoypic calls, with features (SNPs) corresponding to rows and samples to columns), `callProbability`, `G`, `R`, `phenoData`, `experimentData`, and `annotation`. `phenoData`, `experimentData`, and `annotation` can be missing, in which case they are assigned default values.

### Slots

Inherited from `Biobase:eSet`:

`assayData`:

  Contains matrices with equal dimensions, and with column number equal to `nrow(phenoData)`. `assayData` must contain a matrix `call` with rows representing features (e.g., SNPs) and columns representing samples, a matrix `callProbability` describing the certainty of the call, and matrices `R` and `G` to describe allele specific intensities. The contents of these matrices are not enforced by the class. The `assayData` matrices `Gb, Rb, intensity, theta` are optional, but are either results or input for several methods of the class. Additional matrices of identical size may also be included in `assayData`. Class:`AssayData`.

`phenoData`:

  See `eSet`.

`experimentData`:

  See `eSet`.

`annotation`:

  See `eSet`.

`featureData`:

  annotation for SNPs, usually will contain a `CHR` and a `MapInfo` column for genomic localization.

### Methods

Class-specific methods:

`exprs(SnpSetIllumina)`, `exprs(SnpSetIllumina,matrix)<-`

  Access and set elements named `call` in the `AssayData` slot.

`combine(SnpSetIllumina,SnpSetIllumina)`:

  performs `union`-like combination in both dimensions of SnpSetIllumina objects.

`fData(SnpSetIllumina)`, `fData(SnpSetIllumina,data.frame)<-`

  Access and set the `pData` in the featureData slot.

`calculateGSR(SnpSetIllumina)`

  calculate ratio of Gentrain score and Gencall score. Creates GSR matrix in `assayData`. Should be performed before combining datasets.

`calculateSmooth(object,smoothType)`

  calculate smoothed data, creates `smoothed` matrix in `assayData`. `smoothType` can only be "quantsmooth" at the moment

`sortGenomic(SnpSetIllumina)`

  order the data by chromosome and position on the chromosome.

Derived from `eSet`:

`sampleNames(SnpSetIllumina)` and `sampleNames(SnpSetIllumina)<-`:

  See `eSet`.

`featureNames(SnpSetIllumina)`, `featureNames(SnpSetIllumina, value)<-`:

  See `eSet`.

`dims(SnpSetIllumina)`:

  See `eSet`.

`phenoData(SnpSetIllumina)`, `phenoData(SnpSetIllumina,value)<-`:

  See `eSet`.

`varLabels(SnpSetIllumina)`, `varLabels(SnpSetIllumina, value)<-`:

  See `eSet`.

`varMetadata(SnpSetIllumina)`, `varMetadata(SnpSetIllumina,value)<-`:

  See `eSet`.

`pData(SnpSetIllumina)`, `pData(SnpSetIllumina,value)<-`:

  See `eSet`.

`varMetadata(SnpSetIllumina)`, `varMetadata(SnpSetIllumina,value)`

  See `eSet`.

`experimentData(SnpSetIllumina)`,`experimentData(SnpSetIllumina,value)<-`:

  See `eSet`.

`pubMedIds(SnpSetIllumina)`, `pubMedIds(SnpSetIllumina,value)`

  See `eSet`.

`abstract(SnpSetIllumina)`:

  See `eSet`.

`annotation(SnpSetIllumina)`, `annotation(SnpSetIllumina,value)<-`

  See `eSet`.

`storageMode(eSet)`, `storageMode(eSet,character)<-`:

  See `eSet`.

`featureData(SnpSetIllumina)`, `featureData(SnpSetIllumina,AnnotatedDataFrame)<-`

  See `eSet`.

`object[(index)`:

  Conducts subsetting of matrices and phenoData and featureData components.

Standard generic methods:

`initialize(SnpSetIllumina)`:

  Object instantiation, used by `new`; not to be called directly by the user.

`validObject(SnpSetIllumina)`:

  Validity-checking method, ensuring that `call`, `callProbability`, `G`, and `R` are members of `assayData`. `checkValidity(SnpSetIllumina)` imposes this validity check, and the validity checks of `Biobase:class.eSet`.

`show(SnpSetIllumina)`

  See `eSet`.

`dim(SnpSetIllumina)`, `ncol`

  See `eSet`.

`SnpSetIllumina[(index)`:

  See `eSet`.

`SnpSetIllumina$`, `SnpSetIllumina$<-`

  See `eSet`.

### Author(s)

J. Oosting, based on Biobase eSet class

### See Also

`eSet`

[Package beadarraySNP version 1.46.0 Index]