rma-methods {oligo} | R Documentation

## RMA - Robust Multichip Average algorithm

### Description

Robust Multichip Average preprocessing methodology. This strategy allows background subtraction, quantile normalization and summarization (via median-polish).

### Usage

      ## S4 method for signature 'ExonFeatureSet'
    rma(object, background=TRUE, normalize=TRUE, subset=NULL, target="core")
      ## S4 method for signature 'HTAFeatureSet'
    rma(object, background=TRUE, normalize=TRUE, subset=NULL, target="core")
      ## S4 method for signature 'ExpressionFeatureSet'
    rma(object, background=TRUE, normalize=TRUE, subset=NULL)
      ## S4 method for signature 'GeneFeatureSet'
    rma(object, background=TRUE, normalize=TRUE, subset=NULL, target="core")
      ## S4 method for signature 'SnpCnvFeatureSet'
    rma(object, background=TRUE, normalize=TRUE, subset=NULL)

### Arguments

`object` | Exon/HTA/Expression/Gene/SnpCnv-FeatureSet object.
`background` | Logical - perform RMA background correction?
`normalize` | Logical - perform quantile normalization?
`subset` | To be implemented.
`target` | Level of summarization (only for Exon/Gene arrays)

### Methods

`signature(object = "ExonFeatureSet")`

  When applied to an `ExonFeatureSet` object, `rma` can produce summaries at different levels: probeset (as defined in the PGF), core genes (as defined in the core.mps file), full genes (as defined in the full.mps file) or extended genes (as defined in the extended.mps file). To determine the level for summarization, use the `target` argument.

`signature(object = "ExpressionFeatureSet")`

  When used on an `ExpressionFeatureSet` object, `rma` produces summaries at the probeset level (as defined in the CDF or NDF files, depending on the manufacturer).

`signature(object = "GeneFeatureSet")`

  When applied to a `GeneFeatureSet` object, `rma` can produce summaries at different levels: probeset (as defined in the PGF) and 'core genes' (as defined in the core.mps file). To determine the level for summarization, use the `target` argument.

`signature(object = "HTAFeatureSet")`

  When applied to a `HTAFeatureSet` object, `rma` can produce summaries at different levels: probeset (as defined in the PGF) and 'core genes' (as defined in the core.mps file). To determine the level for summarization, use the `target` argument.

`signature(object = "SnpCnvFeatureSet")`

  If used on a `SnpCnvFeatureSet` object (ie., SNP 5.0 or SNP 6.0 arrays), `rma` will produce summaries for the CNV probes. Note that this is an experimental feature for internal (and quick) assessment of CNV probes. We recommend the use of the 'crlmm' package, which contains a Copy Number tool specifically designed for these data.

### References

Rafael. A. Irizarry, Benjamin M. Bolstad, Francois Collin, Leslie M. Cope, Bridget Hobbs and Terence P. Speed (2003), Summaries of Affymetrix GeneChip probe level data Nucleic Acids Research 31(4):e15

Bolstad, B.M., Irizarry R. A., Astrand M., and Speed, T.P. (2003), A Comparison of Normalization Methods for High Density O ligonucleotide Array Data Based on Bias and Variance. Bioinformatics 19(2):185-193

Irizarry, RA, Hobbs, B, Collin, F, Beazer-Barclay, YD, Antonellis, KJ, Scherf, U, Speed, TP (2003) Exploration, Normalizati on, and Summaries of High Density Oligonucleotide Array Probe Level Data. Biostatistics. Vol. 4, Number 2: 249-264

### See Also

`snprma`

### Examples

    if (require(maqcExpression4plex) & require(pd.hg18.60mer.expr)){
    xysPath <- system.file("extdata", package="maqcExpression4plex")
    xysFiles <- list.xysfiles(xysPath, full.name=TRUE)
    ngsExpressionFeatureSet <- read.xysfiles(xysFiles)
    summarized <- rma(ngsExpressionFeatureSet)
    show(summarized)
    }

[Package oligo version 1.44.0 Index]