compute.RA {FLUSH.LVS.bundle}R Documentation

LVS function for the residual standard errors and the array effects

Description

Given an AffyBatch object fits a robust linear model at probe level and return the residual standard errors and the array effects.

Usage

compute.RA(abatch,bg.RA=c("nome","imm","rma"))

Value

an object of class RA with a 'data' slot containing a two columns data.frame with IDs as rows and RSE and Array effects as columns.

Author(s)

Stefano Calza <calza@med.unibs.it>, Davide Valentini and Yudi Pawitan.

References

S. Calza et al. 'Normalization of oligonucleotide arrays based on the least variant set of genes' (2008, BMCBioinformatics).

See Also

lvs, normalize.lvs, lvs.fit, normalize.AffyBatch.lvs fitRA

Examples

## Not run: 
# Starting from an Affibatch object called aBatch 
data.RA <- compute.RA(aBatch)
lvs.id <- lvs.fit(data.RA, proportion=0.6)
lvs.prep <- expresso(aBatch, normalize=FALSE, bgcorrect.method="mas",pmcorrect.method="mas",summary.method="mas")
normalize.AffyBatch.lvs(lvs.prep,lvs.id=lvs.id)
 
## End(Not run)

[Package FLUSH.LVS.bundle version 1.3.1 Index]