GeneSelector {GeneSelector} | R Documentation

## Exclude genes from being candidates for differential expression

### Description

`GeneRankings` and `AggregatedRankings` from several statistics are unified. According to a user-defined or adaptively determined threshold via multiple testing procedures, all genes are checked whether they fall below this threshold consistenly in all statistics used. If this criterion is not met, then the gene is selected.
A final order of the genes is defined by the following criteria

1.
  A user-defined ranking of the used statistics, i.e. the user decides which statistic is most important
2.
  'Selection', i.e. falling below the threshold yes/no
3.
  The obtained ranks. The rank from the most important statistic is considered, then that from the second most important, and so on.

### Usage

    GeneSelector(Rlist, ind = NULL, indstatistic = 1:length(Rlist),
                threshold = c("user", "BH", "qvalue", "Bonferroni", "Holm",
                "Hochberg", "SidakSS", "SidakSD", "BY"),
                maxrank = NULL, maxpval = 0.05)

### Arguments

`Rlist` | A list of objects of class `RepeatedRanking` or `AggregatedRanking`, all based on the same data.
`ind` | Indices of genes to be considered. Defaults to all.
`indstatistic` | An index vector defining the importance of the elements of `Rlist` (typically this is the importance of the used statistics). For instance, if `RList` consists of five elements, then `indstatistic=c(2,4,1,3,5)` would give most importance to the second statistic.
`threshold` | How the threshold is determined. Can be either `"user"` (then the threshold is specified via `maxrank`) or a multiple testing procedure (s. AdjustPvalues). In this case, the p-values of that element of `Rlist` attributed most importance (s. `indtstatistic`) are adjusted and the number of p-values falling below `maxpval` is used as threshold rank. If the most important statistic provides no p-values, then the ones of the second most are used (if available), and so on.
`maxrank` | Specified if `threshold="user"`. A positive integer that is regarded as threshold rank.
`maxpval` | Specified if `threshold` is not `user`

### Value

An object of class CombinedRanking.

### Author(s)

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

### See Also

GeneRanking, AggregatedRanking

### Examples

    ## Load toy gene expression data
    data(toydata)
    ### class labels
    yy <- toydata[1,]
    ### gene expression
    xx <- toydata[-1,]
    ### Get Rankings from five different statistics
    ordinaryT <- RankingTstat(xx, yy, type="unpaired")
    baldilongT <- RankingBaldiLong(xx, yy, type="unpaired")
    samT <- RankingSam(xx, yy, type="unpaired")
    wilc <- RankingWilcoxon(xx, yy, type="unpaired")
    wilcebam <- RankingWilcEbam(xx, yy, type="unpaired")
    ### form a list
    LL <- list(ordinaryT, baldilongT, samT, wilc, wilcebam)
    ### order statistics (assign importance)
    ordstat <-  c(3,4,2,1,5)
    ### start GeneSelector, threshold set to rank 50
    gk50 <- GeneSelector(LL, indstatistic=ordstat, maxrank=50)
    ### start GeneSelector, using adaptive threshold based on p-values,
    ### here using the multiple testing procedure of Hochberg
    gkpval <- GeneSelector(LL, indstatistic=ordstat, threshold = "BH", maxpval=0.05)
    ### show results
    show(gkpval)
    str(gkpval)
    toplist(gkpval)
    ### which genes have been selected ?
    SelectedGenes(gkpval)
    ### relative distance plot
    plot(gkpval, top=5)
    ### Detailed information about gene 4
    GeneInfoScreen(gkpval, which=4)

[Package GeneSelector version 1.2.0 Index]