tigre-package {tigre} | R Documentation

## tigre - Transcription factor Inference through Gaussian process Reconstruction of Expression

### Description

This package implements the method of Gao et al. (2008) and Honkela et al. (2010) for Gaussian process modelling single input motif regulatory systems with time-series expression data. The method can be used to rank potential targets of transcription factors based on such data.

### Details

Package: | tigre
Type: | Package
Version: | 1.12.0
Date: | 2012-10-02
License: | A-GPL Version 3

For details of using the package please refer to the Vignette.

### Author(s)

Antti Honkela, Pei Gao, Jonatan Ropponen, Miika-Petteri Matikainen, Magnus Rattray, Neil D. Lawrence

Maintainer: Antti Honkela <antti.honkela@hiit.fi>

### References

A.~Honkela, P.~Gao, J.~Ropponen, M.~Rattray, and N.~D.~Lawrence. tigre: Transcription factor Inference through Gaussian process Reconstruction of Expression for Bioconductor. Bioinformatics 27(7):1026-1027, 2011. DOI: 10.1093/bioinformatics/btr057.

P.~Gao, A.~Honkela, M.~Rattray, and N.~D.~Lawrence. Gaussian process modelling of latent chemical species: applications to inferring transcription factor activities. Bioinformatics 24(16):i70–i75, 2008. DOI: 10.1093/bioinformatics/btn278.

A.~Honkela, C.~Girardot, E.~H. Gustafson, Y.-H. Liu, E.~E.~M. Furlong, N.~D. Lawrence, and M.~Rattray. Model-based method for transcription factor target identification with limited data. Proc Natl Acad Sci USA 107(17):7793-7798, 2010. DOI: 10.1073/pnas.0914285107.

### See Also

`puma`

### Examples

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

      # Get the target probe names
      library(annotate)
      aliasMapping <- getAnnMap("ALIAS2PROBE",
                        annotation(drosophila_gpsim_fragment))
      twi <- get('twi', env=aliasMapping)
      fbgnMapping <- getAnnMap("FLYBASE2PROBE",
                       annotation(drosophila_gpsim_fragment))
      targetProbe <- get('FBgn0035257', env=fbgnMapping)

      # Learn the model
      model <- GPLearn(drosophila_gpsim_fragment,
                       TF=twi, targets=targetProbe,
                       useGpdisim=TRUE, quiet=TRUE)

      # Plot it
      GPPlot(model, nameMapping=getAnnMap("FLYBASE",
                       annotation(drosophila_gpsim_fragment)))

    ## End(Not run)

[Package tigre version 1.48.0 Index]