readChains: Read MCMC Chains
In GRENITS: Gene Regulatory Network Inference Using Time Series

Description Usage Arguments Details Value References See Also Examples

Read MCMC chains for further analysis.

1	read.chain(output.folder, chainNumber)

`output.folder`	Name of folder (including path) where chains are kept
`chainNumber`	Which of the chains will be read

Read chains produced by NonLinearNet, LinearNet, ReplicatesNet_student and ReplicatesNet_gauss for further analysis.

Returns a list of vectors/matrices with the value of the variables at each MCMC iteration.

Morrissey, E.R., Juarez, M.A., Denby, K.J. and Burroughs, N.J. 2010. On reverse engineering of gene interaction networks using time course data with repeated measurements. Bioinformatics 2010; doi: 10.1093/bioinformatics/btq421

Morrissey, E.R., Juarez, M.A., Denby, K.J. and Burroughs, N.J. 2011 Inferring the time-invariant topology of a nonlinear sparse gene regulatory network using fully Bayesian spline autoregression Biostatistics 2011; doi: 10.1093/biostatistics/kxr009

NonLinearNet, LinearNet, ReplicatesNet_student , ReplicatesNet_gauss .

  #############################################
  ## Run inference using one chain
  #############################################
  # Load A. thaliana circadian clock ODE generated data
  data(Athaliana_ODE)
  # Folder where raw runs will be kept and analysed
  output.folder <- paste(tempdir(), "/Example_LinearNet", sep="")
  # Run network inference, place raw results in output.folder
  # Run just one chain for example purpose
  LinearNet(output.folder, Athaliana_ODE, chains = 1)

  ###########################
  ## Read chain 
  ###########################
  chain1 <- read.chain(output.folder, 1)