lvs.fit {FLUSH.LVS.bundle}R Documentation

LVS selection function

Description

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

Usage

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

Arguments

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.
... ...

Value

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

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

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]