RecoveryScore {GeneSelector} | R Documentation

## Stability measures for gene rankings

### Description

Computes the Recovery Score of Pavlidis et al. (s. reference) below. The stability meausre is the proportion of genes that are declared significant (using usually multiple testing procedures) in both the original and the perturbed dataset.

### Usage

    RecoveryScore(RR, method = c("raw", "BH", "qvalue", "Bonferroni", "Holm",
                  "Hochberg", "SidakSS", "SidakSD", "BY"), maxpval = 0.05)

### Arguments

`RR` | An object of class `RepeatRanking`.
`method` | The p-value adjustment method, s. AdjustPvalues. Can also be `"raw"`(default), then no adjustment will be done.
`maxpval` | The maximum p-value at which a gene is still considered significantly differentially expressed (after adjustment).

### Value

A numeric vector of recovery scores for each perturbed dataset.

### Author(s)

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

### References

Pavlidis, P., Li, Q., Noble, W.S. (2003).
The effect of replication on gene expression microarray experiments. Bioinformatics, 19, 1620-1627

### See Also

GetStabilityLm, GetStabilityOverlap

### Examples

    ### Load toy gene expression data
    data(toydata)
    ### class labels
    yy <- toydata[1,]
    ### gene expression
    xx <- toydata[-1,]
    ### get ranking
    ordT <- RankingTstat(xx, yy, type="unpaired")
    ### Generate Leave-One-Out
    loo <- GenerateFoldMatrix(xx, yy, k=1)
    ### Repeat Ranking with t-statistic
    loor_ordT <- GetRepeatRanking(ordT, loo)
    ### Compute Recovery Score
    rs_ordT <- RecoveryScore(loor_ordT, method="BH")

[Package GeneSelector version 1.4.0 Index]