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]