\name{hmm.setup} \alias{hmm.setup} \title{ Wrapper for computing emission and transition probabilities needed for fitting the hidden Markov model. } \description{ Computes emission probabilities and transition probabilities. See details. } \usage{ hmm.setup(object, states = paste("state", 1:length(copynumberStates), sep = ""), ICE = FALSE, copyNumber = TRUE, copynumberStates = 0:4, EMIT.THR = -10, scaleSds = TRUE, verbose = TRUE, log.initial = log(rep(1/length(states), length(states))), normalIndex = 3, prGenotypeHomozygous = numeric(), prGenotypeMissing = rep(1/length(states), length(states)), pHetCalledHom = 0.001, pHetCalledHet = 0.995, pHomInNormal = 0.8, pHomInRoh = 0.999, rohStates = logical(), trioHmm = FALSE, ...) } \arguments{ \item{object}{ The object must be one of the following classes inherited from \code{eSet} and defined in the R package oligoClasses: \code{SnpSet}, \code{oligoSnpSet}, \code{CopyNumberSet}, or \code{CNSet}. } \item{states}{ Vector of names for the hidden states. } \item{ICE}{ If the object is of class \code{oligoSnpSet} or \code{SnpSet} and the R package crlmm was used to call genotypes, the computed emission probabilities incorporate the confidence estimates of the genotype calls. } \item{copyNumber}{ Logical. Whether to include information on copy number in the hidden Markov model. If the object if of class \code{SnpSet}, this argument is set to FALSE. } \item{copynumberStates}{ Numerical vector with same length as the number of \code{states}. Each value corresponds to the latent copy number of the hidden state. Note that copynumberStates must be specified on the appropriate scale. If the copy number estimates have been log-transformed, the copynumberStates must be provided on the log-scale. } \item{EMIT.THR}{ Single point outliers can cause the HMM to be jumpy. Emission probabilities below EMIT.THR are set to EMIT.THR. } \item{scaleSds}{ Logical. For objects of class \code{CNSet}, sd estimates for total copy number are obtained by using \code{robustSds} function. } \item{verbose}{ Logical. Verbose output during calculations. } \item{log.initial}{ Numeric vector of initial state probabilities (log-scale) corresponding to the hidden states. Must be the same length as \code{states}. } \item{normalIndex}{ Integer. \code{states[normalIndex]} should return the name of the 'normal' hidden state, which in general corresponds to copy number 2. For instance, if the states were "hemizygousDeletion", "normal", and "amplification", normalIndex is 2. } \item{prGenotypeHomozygous}{ Numeric. The probability of a homozygous genotype call in each of the hidden states. Ignored if ICE is TRUE. } \item{prGenotypeMissing}{ Numeric. The probability of a missing genotype for each hidden states. } \item{pHetCalledHom}{ Numeric. Probability of misclassifying a genotype call as heterozygous if the true genotype is homozygous. Ignored unless ICE is TRUE. } \item{pHetCalledHet}{ Numeric. Probability of correctly classifying a genotype call as heterozygous. Ignored unless ICE is TRUE. } \item{pHomInNormal}{ Numeric. Probability of a homozygous genotype in a region without loss of heterozygosity. Ignored unless ICE is TRUE. } \item{pHomInRoh}{ Numeric. Probability of a homozygous genotype in a 'region of homozygosity'. Ignored unless ICE is TRUE. } \item{rohStates}{ Logical vector. TRUE corresponds to a hidden states in which regions of homozygosity are expected. For instance, regions of homozygosity would be TRUE for hidden states corresonding to copy-neutral region of homozygosity (as my occur in a loss of heterozygosity region) and hemizygous deletions. } \item{trioHmm}{ Logical. This option is experimental. For Father-Mother-Offspring trios, we compute emission probabilities for biparental inheritance where the genotypes are informative. The hidden states correspond to biparental inheritance or non-biparental inheritance. Regions of non-biparental inheritance can be used to quickly flag regions that are possibly de-novo deletions. } \item{\dots}{ Ignored. } } \details{ Details on the calculation of emission probabilities. } \value{ } \author{ R. Scharpf } \seealso{ \code{\link{robustSds}} } \examples{ } \keyword{models} \keyword{manip}