With the development of analytical methods for multiple-locus parameter estimation and the relative ease of collecting large amounts of sequence data, researchers with limited resources are concerned increasingly with how much data is required to estimate the parameters of interest accurately [17].
In the analysis of the combined loci, parameter estimates of each locus were unlinked, allowing independent substitution models for each locus.
The percentiles adjusted for the baseline expected under the neutral scenario give a less biased estimate of multi-locus parameter deviations than the raw data, while the large number of resampling allows an estimation of the chance of observing each rare combination of sequential values without additional models or assumptions.
For priors of mutation parameters, only the Uniform and the Gamma distributions are considered, but hierarchical schemes are possible, with a mean mutation rate or coefficient P (of the geometric distribution in the GSM) drawn from a given prior and individual loci parameter values drawn from a gamma distribution around the mean.
Marker loci parameters (map position, number of alleles, observed informative meioses etc).
For each locus, the parameters of the overlapped clones were assigned.
Bayesian analyses for the combined data set were performed in a partitioned framework, allowing locus-specific parameter estimation.
A loci grouping threshold of LOD≥8 was used with default locus ordering parameters.
For each gene, the mutation rate μ was estimated from the per-locus mutation parameter ?
For each gene, the mutation rate μ was estimated from the per-locus mutation parameter observed for the susceptible strain (θ = 4 Neμ and Ne = 6000) and used as the starting value for the simulations.
Examination of publically available data of several large GWAS consortia for association of the locus with parameters related to glucose and fat metabolism provided as yet no clues for other potentially involved mechanisms.
