RankingLimma {GeneSelector} | R Documentation

## Ranking based on the 'moderated' t statistic

### Description

The 'moderated' t statistic is based on a Bayesian hierarchical model which is estimated by an empirical Bayes approach (Smyth et al., 2003). The function is a wrapper to the functions `fitLm` and `eBayes` implemented in the `limma` package.

### Usage

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

### Arguments

`x` | A `matrix` of gene expression values with rows corresponding to genes and columns corresponding to observations or 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 passed to the function `eBayes`, for instance the prior probability for differential expression. Consult the help of the `limma` package for details

### Value

An object of class GeneRanking.

### Author(s)

Martin Slawski
Anne-Laure Boulesteix

### References

Smyth, G. K., Yang, Y.-H., Speed, T. P. (2003).
Statistical issues in microarray data analysis. Methods in Molecular Biology 2:24, 111-136.

### See Also

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

### Examples

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

[Package GeneSelector version 2.30.0 Index]