GetStabilityLm {GeneSelector} | R Documentation |
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.
GetStabilityLm(RR, decay = c("linear", "quadratic", "exponential"), measure = c("wilks", "direct"), scheme = c("rank", "pval"), alpha = 1, ...)
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 . |
An object of class GetStabilityLm
Martin Slawski martin.slawski@campus.lmu.de
Anne-Laure Boulesteix http://www.slcmsr.net/boulesteix
Mardia, K.V., Kent, J.T., Bibby, J.M. (1979).
Multivariate Analysis Academic Press.
GetRepeatRanking, GetStabilityOverlap, RecoveryScore, GetAlpha
### 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 )