lvs: LVS Normalization

In biostatUniBS/FLUSH.LVS.bundle: FLUSH.LVS.bundle

Description

Performs a normalization of oligonucleotide arrays based on the Least Variant Set of genes.

Usage

lvs(aBatch, proportion = 0.6, bgcorrect.method = "mas", pmcorrect.method = "mas", summary.method = "mas")

Arguments

aBatch	an AffyBatch object.
proportion	the proportion below which genes are expected not to vary between samples. Default is set to 0.6.
bgcorrect.method	a background correction method among methods available in expresso function. Default is set to mas5.
pmcorrect.method	a PM correction method among methods available in expresso function. Default is set to mas5.
summary.method	a summarization method among methods available in expresso function. Default is set to mas5.

Details

This function performs a complete LVS procedure (see references) starting from an AffyBatch object, wrapping compute.RA, lvs.fit and normalize.AffyBatch.lvs functions. As a first step it selects Least Variant genes, then it preprocess and summarize the affybatch, using mas5 as default, and finally it normalize the data according to LVS procedure (taking into account identified Least Variant genes as reference Set), reporting expression measures. The default proportion is set to 0.6, accordingly to the experience that no more than 40% of genes vary between arrays.

Value

an ExpressionSet object, containing the LVS normalized values, with expression measures.

Author(s)

Stefano Calza <[e-mail]>, 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

normalize.lvs, compute.RA, lvs.fit, expresso, read.affybatch

Examples

## Not run: 
# Download and install Choe data package from http://www.meb.ki.se/~yudpaw/
data(choe)
data.norm <- lvs(choe)

## End(Not run)

biostatUniBS/FLUSH.LVS.bundle documentation built on May 28, 2019, 4:34 p.m.