clusterSignifFDR-class {goCluster} | R Documentation

## Class "clusterSignifFDR"

### Description

This class provides a selection mechanism that uses the false dicovery rate (FDR) to identify annotation terms which are significantly enriched in selected gene groups.

### Details

The class provides a wrapper around the `randomizeTree`, `mergeAnno`, and `selectAnnoStats` function. Please read the corresponding documentation for further details.

### Slots

`threshold`:
  Object of class `"numeric"`, this specifies the fraction of selected annotation elements that would also be identified from random data. The class will select as many elements as possible until this threshold is reached.
`randomstat`:
  Object of class `"list"`, a list of p-values for a number of randomized datasets with the same structure as the original data.
`repeats`:
  Object of class `"numeric"`, specifies the number of randomized datasets that will be generated to calculate the false discovery rate.
`pthresholds`:
  Object of class `"numeric"`, these are the p-value-thresholds for the selection. The FDR-threshold (see above) is transformed into a p-value threshold by determining how many elements can be selected without exceeding the given threshold of false positives. Since this is done for each annotation dataset this holds a vector of thresholds.

Additional slots are described in the documentation of the `clusterSignif-class` and `clusterModule-class`.

### Extends

Class `"clusterSignif"`, directly. Class `"clusterModule"`, by class `"clusterSignif"`.

### Methods

config
  `signature(object = "clusterModule")`: interactive setup of the class. You can set the FDR threshold here.
setup
  `signature(object = "clusterModule")`: returns the configuration of the object as a list. This list can be used for the non-interactive setup of the class.
setup<-
  `signature(object = "clusterModule")`: non-interactive setup of the class. You need to provide a list that contains the necessary settings for the class.
execute
  `signature(object = "clusterModule")`: selects as many annotation terms as possible without exceeding the specified FDR.
reset
  `signature(object = "clusterModule")`: resets the results of this class so that the selection process can be run again.

### Author(s)

Gunnar Wrobel, http://www.gunnarwrobel.de.

### See Also

`selectAnnoStats`, `randomizeTree`, `mergeAnno`, `goCluster-class`, `clusterSignif-class`, `clusterModule-class`

[Package goCluster version 1.0.0 Index]