'k' files are created (where 'k' is the number of different
models fitted in 'obj') in the working directory.
Each file contains as many rows as MCMC samples for that
model. Each row describes the hidden state sequence, in the
format 'state', '', 'breakpoint position', etc. until a
'-1' showing the end of the sequence and a final number,
the times that that particular path has occurred in the
MCMC.
'k' files are created with names 'filename' plus the number
of the model (in fact, the number of hidden states in that
model.
Rueda OM, Diaz-Uriarte R.
Flexible and Accurate Detection of Genomic Copy-Number Changes from
aCGH.
PLoS Comput Biol. 2007;3(6):e122
[object Object],[object Object]RJaCGH, link{pMCR}, link{prob.seq},
pREC_A, pREC_S
y <- c(rnorm(100, 0, 1), rnorm(10, -3, 1), rnorm(20, 3, 1),
rnorm(100,0, 1))
Pos <- sample(x=1:500, size=230, replace=TRUE)
Pos <- cumsum(Pos)
Chrom <- rep(1:23, rep(10, 23))
jp <- list(sigma.tau.mu=rep(0.5, 4), sigma.tau.sigma.2=rep(0.3, 4),
sigma.tau.beta=rep(0.7, 4), tau.split.mu=0.5, tau.split.beta=0.5)
fit.genome <- RJaCGH(y=y, Pos=Pos, Chrom=Chrom, model="genome",
burnin=10, TOT=1000, k.max = 4,
jump.parameters=jp)
getSequence(fit.genome, 'sequence', 'Gain')
models