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MORGAN can obtain a starting configuration for S in one of two ways. The default method is by sequential imputation. The alternative is to contruct an L-sampler realization independently for each locus, conditional on the genotype data at that locus only (the locus-by-locus option). Sequential imputation tends to produce initial configurations that have higher conditional probabilities, but locus-by-locus sampling can sometimes reveal other modes in the complex space of S values. The MORGAN user can select the L-sampler setup method by including the `use locus-by-locus for setup' statement. If sequential imputation is selected, the user can specify the number of sequential imputation samples from which the starting configuration of meiosis indicators is to be selected, using the `use I sequential imputation realizations for setup' statement. The default is 10% of the total MC iterations.
At each MCMC iteration, MORGAN selects a locus (with L-sampler) or meiosis (with M-sampler) to update. Two different selection methods are available: sample by step and sample by scan. If `sample by scan' is chosen, all loci or meioses are updated one-at-a-time in a predetermined random order. This option is the default. If `sample by step' is chosen, a single locus or meiosis is randomly selected for updating at each iteration. The sampling method selected applies to the entire MCMC run, including burn-in, pseudo-prior computation and main iterations.
When running a MORGAN MCMC program, the user must specify the
desired number of several types of iterations. For all programs, some
number of initial burn-in iterations must be performed. These
realizations are discarded and, if the burn-in period is sufficiently
long, subsequent points will be dependent samples from the desired
stationary distibution. The `set burn-in iterations' statement is
used to specify the number of desired burn-in iterations, with the
default value varying by program. The
desired number of "main" iterations must be specified using the
`set MC iterations' statement; there is no default number of main
iterations. Recommended number of iterations is on the order of
10^5. lm_bayes performs a third type of iteration to
calculate pseudo-priors. Alternatively, pseudo-priors can be read from
an input file. They encourage the MC sampler to visit test positions of
low conditional probability. The number of iterations for calculation
of pseudo-priors is set using the `set pseudo-prior iterations'
statement, or the default value of 50% of the number of main iterations
can be used.
Specific Autozyg and Lodscore programs have additional parameters and
options that are described in the relevant sections of the next two
chapters of the tutorial.
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