GPPlot: Plot GP(DI)SIM models

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

Description

Plots GP(DI)SIM models.

Usage

GPPlot(data, savepath = '', nameMapping = NULL, predt = NULL,
       fileOutput=FALSE, plotTime=NULL)

Arguments

data	The model to plot as returned by GPLearn.
savepath	The location in the file system where the images are saved.
nameMapping	The annotation used for mapping the names of the genes for the figures.
predt	The set of time points to use in plotting (default: the time interval covering the data).
fileOutput	Is the plot being saved to a file? If yes, do not open new interactive devices for each plot.
plotTime	The times of observations to use in the plot. Should usually not be changed!

Details

The function plots the fitted expression level of the transcription factor (if applicable), the inferred activity of the transcription factor, and the fitted expression level of the target(s).

Author(s)

Antti Honkela

See Also

GPLearn.

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)

tigre documentation built on Nov. 8, 2020, 5:32 p.m.