RankingFoxDimmic {GeneSelector} | R Documentation

## Ranking based on the t-statistic of Fox and Dimmic

### Description

Performs a two-sample bayesian t test on a gene expression matrix using the methodology by Fox and Dimmic (2006).
For `S4` method information, see RankingFoxDimmic-methods.

### Usage

    RankingFoxDimmic(x, y, type = "unpaired", m = 8, pvalues = TRUE, 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`.
`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`.
`type` | "unpaired": two-sample test, equal variances assumed. `"paired"` and `"unpaired"` are not possible for this kind of test.
`m` | The number of similarly expressed genes to use for calculating Bayesian variance and prior degrees of freedom. The default value suggested by Fox and Dimmic is currently 8, s. note.
`pvalues` | Should p-values be computed ? Default is `TRUE`.
`gene.names` | An optional vector of gene names.
`...` | Currently unused argument.

### Value

An object of class GeneRanking.

### Note

Although the test of Fox and Dimmic is very similar to the one proposed by Baldi and Long, there are various slight differences, in particular with respect to the computation of the bayesian variance.

### Author(s)

Martin Slawski martin.slawski@campus.lmu.de
Anne-Laure Boulesteix http://www.slcmsr.net/boulesteix

### References

Fox, R.J., Dimmic, M.W. (2006).
A two sample Bayesian t-test for microarray data. BMC Bioinformatics, 7:126

### See Also

GetRepeatRanking, RankingTstat, RankingFC, RankingWelchT, RankingWilcoxon, RankingBaldiLong, RankingLimma, RankingEbam, RankingWilcEbam, RankingSam, RankingBstat, RankingShrinkageT, RankingSoftthresholdT, RankingPermutation, RankingGap

### Examples

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

[Package GeneSelector version 1.2.0 Index]