RankingWilcEbam: Ranking based on the empirical bayes approach of Efron
In GeneSelector: Stability and Aggregation of ranked gene lists

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

The function is a wrapper for the function wilc.ebam from the package siggenes that implements an empirical bayes mixture model approach in combination with the Wilcoxon statistic.

1	RankingWilcEbam(x, y, type = c("unpaired", "paired", "onesample"), gene.names = NULL, ...)

`x`	A `matrix` of gene expression values with rows corresponding to genes and columns corresponding to observations or alternatively an object of class `ExpressionSet` alternatively an object of class `ExpressionSet`. If `type = paired`, the first half of the columns corresponds to the first measurements and the second half to the second ones. For instance, if there are 10 observations, each measured twice, stored in an expression matrix `expr`, then `expr[,1]` is paired with `expr[,11]`, `expr[,2]` with `expr[,12]`, and so on.
`y`	If `x` is a matrix, then `y` may be a `numeric` vector or a factor with at most two levels. If `x` is an `ExpressionSet`, then `y` is a character specifying the phenotype variable in the output from `pData`. If `type = paired`, take care that the coding is analogously to the requirement concerning `x`
`type`	"unpaired": two-sample test. "paired": paired test. Take care that the coding of `y` is correct (s. above) "onesample": `y` has only one level. Test whether the true mean is different from zero.
`gene.names`	An optional vector of gene names.
`...`	Further arguments to be passed to `wilc.ebam`, s. package `siggenes`.

An object of class GeneRanking.

p-values are not computed - the statistic is a posterior probabiliy.

Martin Slawski
Anne-Laure Boulesteix

Efron, B., Tibshirani, R. (2002).
Empirical Bayes Methods and False Discovery Rates for Microarrays Genetic Epidemiology, 23, 70-86

Schwender, H., Krause, A. and Ickstadt, K. (2003).
Comparison of the Empirical Bayes and the Significance Analysis of Microarrays. Techical Report, University of Dortmund.

RepeatRanking, RankingTstat, RankingFC, RankingWelchT, RankingWilcoxon, RankingBaldiLong, RankingFoxDimmic, RankingLimma, RankingEbam, RankingSam, RankingShrinkageT, RankingSoftthresholdT, RankingPermutation

### Load toy gene expression data
data(toydata)
### class labels
yy <- toydata[1,]
### gene expression
xx <- toydata[-1,]
### run RankingWilcEbam
WilcEbam <- RankingWilcEbam(xx, yy, type="unpaired")