RankingFoxDimmic {GeneSelector} | R Documentation |
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.
RankingFoxDimmic(x, y, type = "unpaired", m = 8, 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 |
"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. |
An object of class GeneRanking.
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.
Martin Slawski martin.slawski@campus.lmu.de
Anne-Laure Boulesteix http://www.slcmsr.net/boulesteix
Fox, R.J., Dimmic, M.W. (2006).
A two sample Bayesian t-test for microarray data.
BMC Bioinformatics, 7:126
GetRepeatRanking, RankingTstat, RankingFC, RankingWelchT, RankingWilcoxon, RankingBaldiLong, RankingLimma, RankingEbam, RankingWilcEbam, RankingSam, RankingBstat, RankingShrinkageT, RankingSoftthresholdT, RankingPermutation, RankingGap
## 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")