compute-methods: Compute the eigensystem for a feature by assay matrix
In biosvd: Package for high-throughput data processing, outlier detection, noise removal and dynamic modeling

Description Usage Arguments Details Value Methods Author(s) References See Also Examples

Computes the eigensystem for a feature by assay matrix by applying Singular Value Decomposition.

1 2	## S4 method for signature 'Eigensystem' compute(object, apply = c("data", "variance"))

`object`	object of class matrix, data.frame, Expressionset or Eigensystem, containing the feature x assay expression or intensity data
`apply`	the actual expression/intensity data (data) or variance in the data (variance) to which to apply the function (default = data)

Function compute decomposes the input data set from the feature x assay space to the reduced diagonalized "eigenfeatures x eigenassays" space, with the eigenfeatures and eigenassays unique orthonormal superpositions of the features and assays, respectively. This approach allows filtering out eigenfeatures and eigenassays that are inferred to represent noise or experimental artifacts, either at the expression/intensity level or the variance level. The function can be applied to an object of class matrix, data.frame, ExpressionSet, or eigensystem.

Object of class Eigensystem

signature(x = "Eigensystem")
signature(x = "data.frame")
signature(x = "matrix")
signature(x = "ExpressionSet")

Anneleen Daemen daemen.anneleen@gene.com, Matthew Brauer brauer.matthew@gene.com

Alter O, Brown PO and Botstein D. Singular value decomposition for genome-wide expression data processing and modeling. Proc Natl Acad Sci U.S.A. 97(18), 10101-10106 (2000).

Eigensystem-class

Other X.eigensystem.: exclude, exclude,Eigensystem-method; plot, plot,Eigensystem,EigensystemPlotParam-method; report, report,Eigensystem,EigensystemPlotParam-method

## Metabolomics starvation data obtained from http://genomics-pubs.princeton.edu/StarvationMetabolomics/Download.shtml
data(StarvationData)

## Computes the eigensystem for the actual expression/intensity data
eigensystem <- compute(StarvationData)
## Computes the eigensystem for the variance in the data
eigensystem <- compute(StarvationData, apply="variance")