RankingBaldiLong {GeneSelector} | R Documentation

## Ranking based on the t-statistic of Baldi and Long

### Description

Performs bayesian t tests on a gene expression matrix.
For `S4` method information, see RankingBaldiLong-methods.

### Usage

    RankingBaldiLong(x, y, type = c("unpaired", "paired", "onesample"),
                      m = 100, conf = NULL, 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. "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.
`m` | Size of the sliding window that is used obtain the background variance from pooled similarly expressed genes. s. Details.
`conf` | The number of 'pseudocounts' giving weight to the prior variance. s. Details.
`pvalues` | Should p-values be computed ? Default is `TRUE`.
`gene.names` | An optional vector of gene names.
`...` | Currently unused argument.

### Details

The argument `m` determines the width of the window used to provides an estimate of the average variability of gene expression for those genes that show a similar expression level.
The argument `conf` is non-negative and indicates the weight give to the Bayesian prior estimate of within-treatment variance. Baldi and Long report reasonable performance with this parameter set equal to approximately 3 times the number of observations, when the number of experimental observations is small (approximately 4 or less). If the number of replicate experimental observations is large then the confidence value can be lowered to be equal to the number of observations (or even less).

### Value

An object of class GeneRanking.

### Note

Results can differ slighlty from the Cyber-T-Software of Baldi and Long.

### Author(s)

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

### References

Baldi,P., Long, A.D. (2001).
A bayesian framework for the analysis of microarray data. Bioinformatics, 17, 509-519

### See Also

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

[Package GeneSelector version 1.2.0 Index]