generateModels {tigre} | R Documentation

## Generating models with the given data

### Description

'generateModels' recreates models based on the parameters stored in a scoreList.

### Usage

      generateModels(preprocData, scores)

### Arguments

`preprocData` | The preprocessed data to be used.
`scores` | A scoreList object containing data of the models to be generated.

### Value

'generateModels' returns a list of the generated models.

### Author(s)

Antti Honkela, Jonatan Ropponen

### See Also

`GPLearn, GPRankTargets, GPRankTFs, scoreList`.

### Examples

    ## Not run:
      # Load a mmgmos preprocessed fragment of the Drosophila developmental
      # time series
      data(drosophila_gpsim_fragment)

      # Get the target probe names
      targets <- c('FBgn0003486', 'FBgn0033188', 'FBgn0035257')
      library(annotate)
      aliasMapping <- getAnnMap("ALIAS2PROBE",
                        annotation(drosophila_gpsim_fragment))
      twi <- get('twi', env=aliasMapping)
      fbgnMapping <- getAnnMap("FLYBASE2PROBE",
                       annotation(drosophila_gpsim_fragment))
      targetProbes <- mget(targets, env=fbgnMapping)

      scores <- GPRankTargets(drosophila_gpsim_fragment, TF=twi,
                              testTargets=targetProbes,
                              options=list(quiet=TRUE),
                              filterLimit=1.8)

      models <- generateModels(drosophila_gpsim_fragment, scores)

    ## End(Not run)

[Package tigre version 1.48.0 Index]