gr.normalize: A function for normalization
In geneRecommender: A gene recommender algorithm to identify genes coexpressed with a query set of genes

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

gr.normalize normalizes a matrix of gene expression data as part of the implementation of the Gene Recommender algorithm described in Owen et al (2003). gr.normalize must be applied to the data before running gr.main.

1	gr.normalize(unnormalized.dataset)

unnormalized.dataset

A matrix or ExpressionSet containing the normalized gene expression data. The rows correspond to genes, the columns correspond to experiments, and the entries correspond to the gene expression levels. The rows must be labeled.

gr.normalize normalizes the data so that for each gene, the gene expression measurements are distributed uniformly between -1 and 1.

The normalized gene expression data, in the same format as the input.

Gregory J. Hather ghather@stat.berkeley.edu
with contributions from from Art B. Owen art@stat.stanford.edu
and Terence P. Speed terry@stat.berkeley.edu.

Art B. Owen, Josh Stuart, Kathy Mach, Anne M. Villeneuve, and Stuart Kim. A Gene Recommender Algorithm to Identify Coexpressed Genes in C. elegans. Genome Research 13:1828-1837, 2003.

gr.main, gr.cv

#This example uses the geneData dataset from the Biobase package
data(geneData)
my.query <- c("31730_at", "31331_at", "31712_at", "31441_at")
normalized.data <- gr.normalize(geneData)