GetStabilityLm {GeneSelector} | R Documentation

## Stability measures for gene rankings

### Description

Assesses stability of gene rankings by regressing the rankings of perturbed datasets on the ranking of the original datasets in a weighted manner. The idea is that if stability is high, the resulting regression models fit well.

### Usage

    GetStabilityLm(RR, decay = c("linear", "quadratic", "exponential"),
                    measure = c("wilks", "direct"),
                    scheme = c("rank", "pval"), alpha = 1, ...)

### Arguments

`RR` | An object of class RepeatRanking.
`scheme` | Whether ranks (`scheme="rank"`) or p-values (`scheme="pval"`) should be used as basis of weighting.
`decay` | argument controlling the weight decay for the weights used in the linear regression model. If `decay=linear`, then the weight of the s-th rank/p-value is `1/s`, if `decay=quadratic`, then the weight is `1/s^2` and if `decay=exponential`, then the weight is `exp(-s*alpha)`, where `alpha` is a tuning parameter specified via the argument `alpha`.
`measure` | The stability measure to be computed. If `measure="wilks"`, then a stability measure based on the Wilk's Lambda Test for multivariate linear regression models is used. If `measure="direct"`, then the direct generalization of the univariate coefficient of determination to the multivariate case is used. The second approach can fail if there exists rankings of the perturbed datasets that are exactly equal.
`alpha` | To be specified only if `decay="exponential"`, s. also GetAlpha.
`...` | Further arguments passed to `lm`.

### Value

An object of class `GetStabilityLm`

### Author(s)

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

### References

Mardia, K.V., Kent, J.T., Bibby, J.M. (1979).
Multivariate Analysis Academic Press.

### See Also

GetRepeatRanking, GetStabilityOverlap, RecoveryScore, GetAlpha

### 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)
    ### assess stability
    stab_lm_ordT <- GetStabilityLm(loor_ordT, decay="linear")
    ### plot
    plot(stab_lm_ordT )

[Package GeneSelector version 1.4.0 Index]