mlDNA (version 1.1)

geneRanker: Gene Ranking

Description

This function ranks genes based on differential expression analytic method.

Usage

geneRanker(expmat1, expmat2, genes,  rankers = c("ttest", "SAM", "Limma"), verbose = FALSE)

Arguments

expmat1

a numeric matrix, gene expression matrix under condition 1.

expmat2

a numeric matrix, gene expression matrix under condition 2.

genes

a character vector, genes to be analyzed.

rankers

a character vector, differential expression methods

verbose

logical. TRUE: intermediate results will be printed to the screen.

Value

A list containing different components:

ranker

a numeric matrix containing gene rank, statistic and p-value from the ranker.

dot

a numeric matrix containing gene rank, statistic and p-value from the rankers.

pvalMat

a numeric matrix containing p-values from different rankers.

Details

Different methods can be selected. More information can be referred in GeneSelector package (Boulesteix and Slawski, 2009). To run this function, please first install geneSelector package with the commands: source("http://bioconductor.org/biocLite.R"); biocLite("GeneSelector")

References

[1] Boulesteix A-L and Slawski M. Stability and aggregation of ranked gene lists. Brief Bioinform, 2009, 10(5): 556-568.

Examples

   
## Not run:    
# 
#    ##differential expression analysis
#    res <- geneRanker(expmat1 = ControlExpMat, expmat2 = SaltExpMat, 
#           genes = rownames(ControlExpMat)[1:100], 
#           rankers = c("ttest", "SAM", "Limma"), 
#           verbose = FALSE )
#    
#    ##the p-value for differential method
#    res$pvalMat[1:10,]
# ## End(Not run)