lvs.fit: LVS selection function
In biostatUniBS/FLUSH.LVS.bundle: FLUSH.LVS.bundle

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

Selects the Least Variant Set of genes, accordingly to the chosen proportion of genes expected not to vary between arrays.

1	lvs.fit(object, proportion = 0.6, DF=10,...)

`object`	an object of class RA or a matrix with residual standard errors and array effects.
`proportion`	the proportion below which genes are expected not to vary between samples. Default is set to 0.6.
`DF`	the degrees of freedom used for the bi-spline in the quantile regression.
`...`	`...`

a TRUE/FALSE vector with the seleted ID probes from the quantile regression.

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

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

lvs, normalize.lvs, compute.RA,RA-class, normalize.AffyBatch.lvs

## 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)