generateModels: Generating models with the given data

In ahonkela/tigre: Transcription factor Inference through Gaussian process Reconstruction of Expression

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)

ahonkela/tigre documentation built on Aug. 6, 2021, 12:08 p.m.