Workflow Entry: BATWING

Batwing reads in multi-locus haplotype data, and model and prior distri- bution specifications, and uses a Markov chain Monte Carlo (MCMC) method based on coalescent theory to generate approximate random samples from the posterior distributions of parameters such as mutation rates, effective population sizes and growth rates, and times of population splitting events. It also generates approximate posterior samples of the entire genealogical tree underly- ing the sample, including the tree height, which corresponds to the Time since the Most Recent Common Ancestor (TMRCA). Batwing does not model the effects of either recombination or selection, and hence implicitly assumes that these effects are negligible. Note also that Batwing is intended for within- species data, and not between-species data for which many phylogenetic soft- ware packages are available. Batwing is a direct descendant of MICSAT, described in Wilson & Balding (Genetics 150, pp 499-510, 1998). The principal differences are: (1) in addition to the stepwise mutation model (SMM) for microsatellite loci, there are mu- tation models for unique event polymorphisms (UEP); and (2) the population demography is extended from constant size, random mating, populations (the standard coalescent model), to include population growth and subdivision.

URL: http://www.loni.ucla.edu/twiki/bin/view/LONI/Pipeline_GenomicsInformatics_BATWING?skin=plain#LONI_Pipeline_BATWING_Workflows

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