RankingFoxDimmic: Ranking based on the t-statistic of Fox and Dimmic
In GeneSelector: Stability and Aggregation of ranked gene lists

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

Performs a two-sample Bayesian t test on a gene expression matrix using the method of Fox and Dimmic (2006).

1	RankingFoxDimmic(x, y, type = "unpaired", m = 4, pvalues = TRUE, 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`.
`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 4, s. note.
`pvalues`	Should p-values be computed ? Default is `TRUE`.
`gene.names`	An optional vector of gene names.
`...`	Currently unused argument.

An object of class GeneRanking.

Although the test of Fox and Dimmic is very similar to that of Baldi and Long; there are various slight differences, in particular with respect to the computation of the Bayesian variance.

Martin Slawski
Anne-Laure Boulesteix

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

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

## 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")