RankingTstat {GeneSelector} | R Documentation

## Ranking based on the 'ordinary' t statistic.

### Description

Performs univariate (rowwise) t tests on a gene expression matrix.
For `S4` method information, see RankingTstat-methods.

### Usage

    RankingTstat(x, y, type = c("unpaired", "paired", "onesample"), 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`. 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, equal variances assumed. For unequal variances, use RankingWelchT. "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.
`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.

### Author(s)

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

### See Also

GetRepeatRanking, RankingFC, RankingWelchT, RankingWilcoxon, RankingBaldiLong, RankingFoxDimmic, 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 RankingTstat
    ordT <- RankingTstat(xx, yy, type="unpaired")

[Package GeneSelector version 1.2.0 Index]