SHIP-package {SHIP} | R Documentation |
SHrinkage covariance Incorporating Prior knowledge
Description
The SHIP-package implements the shrinkage estimator of a covariance matrix given any covariance target, such as described by Schaefer and Strimmer in 2005. In addition, it proposes several targets based on biological knowledge extracted from the public database KEGG.
Details
To use the shrinkage estimator, one should just have at hand a data set in
the form of a n \times p
matrix, and a covariance target.
If one wishes to use the proposed targets, the data set should be compatible with KEGG, i.e. it should be possible to extract for each gene the pathways it belongs to. This information, for example, can be found in libraries such as hgu133plus2.db.
Author(s)
Monika Jelizarow and Vincent Guillemot
References
J. Schaefer and K. Strimmer, 2005. A shrinkage approach to large-scale covariance matrix estimation and implications for functional genomics. Statist. Appl. Genet. Mol. Biol. 4:32.
M. Jelizarow, V. Guillemot, A. Tenenhaus, K. Strimmer, A.-L. Boulesteix, 2010. Over-optimism in bioinformatics: an illustration. Bioinformatics. Accepted.
See Also
Useful links:
Examples
# A short example on a toy dataset
# require(SHIP)
data(expl)
attach(expl)
sig1 <- shrink.estim(x,targetD(x))
sig2 <- shrink.estim(x,targetF(x))
sig3 <- shrink.estim(x,targetCor(x,genegroups))
sig4 <- shrink.estim(x,targetG(x,genegroups))
paste(sig1[[2]],collapse=" ")
paste(sig2[[2]],collapse=" ")
paste(sig3[[2]],collapse=" ")
paste(sig4[[2]],collapse=" ")