Description Usage Arguments Value Note Author(s) References See Also Examples

The similarity of *multiple* ordered genelists is assessed
by counting the size of the union ('union count') for each position in the list. The higher the union count, the less stable are the
ordered lists. Similarly to the 'overlap score' of Yang et al. (2006), Lottaz et al. (2006), we compute
a weighted average of the union count entitled 'union score' .

1 2 | ```
GetStabilityUnion(RR, decay = c("linear", "quadratic", "exponential"),
alpha = 1, noinformation = 0,...)
``` |

`RR` |
An object of class |

`decay` |
Argument controlling the weight decay of the weights
used for the computation of the union score. If |

`alpha` |
s. |

`noinformation` |
If |

`...` |
Currently unused argument. |

An object of class StabilityOverlap

Union count and union score are suitably normalized to fall into the unit interval for the sake of better interpretability, with zero corresponding to maximal instability.

Note that this function yields exactly one stability score for multiple lists, as opposed to the pairwise approach in GetStabilityOverlap and GetStabilityDistance.

Martin Slawski

Anne-Laure Boulesteix

Stolovitzky, G. (2003). Gene selection in microarray data: the elephant, the blind men, and our algorithms.
*Current Opinion in Structural Biology 13, 370-376*.

Jurman, G., Merler, S., Barla, A., Paoli, S., Galea, A., Furlanello, C. (2008).

Algebraic stability indicators for ranked lists in molecular profiling. *Bioinformatics 24, 258-264*

Yang, X., Bentink, S., Scheid, S., Spang, R. (2006)

Similarities of ordered gene lists. *Journal of Bioinformatics
and Computational Biology 4, 693-708*

Lottaz, C., Yang, X., Scheid, S., Spang, R. (2006)

OrderedList - a Bioconductor package for detecting
similarity in ordered gene lists.
*Bioinformatics, 22, 2315-2316*

RepeatRanking

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
## 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(y = yy, k=1)
### Repeat Ranking with t-statistic
loor_ordT <- RepeatRanking(ordT, loo)
### assess stability
stab_union_ordT <- GetStabilityUnion(loor_ordT, decay="linear")
### display the result
plot(stab_union_ordT)
``` |

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