Batwing
documentation

(2003)
BATWING is a program written in C for the analysis of population genetic data. BATWING reads in multi-locus haplotype data, and model and prior distribution 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 underlying the sample, including the tree height, which corresponds to the Time since the Most Recent Common Ancestor (TMRCA). Note also that BATWING is intended for within-species data, and not between-species data for which many phylogenetic software packages are available.

• Unix
• Mac OS
• Windows

• Microsat
• SNP
• haploid data

• one line per haplotype, with one or more spaces separating the alleles at distinct loci
• #: the rest of the line is ignored (the whole line is ignored if # is the first non-space character)
• First come the UEP alleles (SNP) which may be coded by any two single alphanumeric characters (e.g. “0” and “1”, or “A” and “T”)
• Next come the microsatellite or STR (= short tandem repeat)
  • coded by an integer value giving the number of tandem repeats at that locus
  • Missing STR data can be specified using −1
• If the data are drawn from several distinct populations:
  • stored in a file locationfile, in the same way as for datafile
  • rows of the locationfile should correspond to the rows of the datafile
  • subpopulation codes may be any positive integers
  • missing location information can be specified using −1

The input file specifies 10 STR loci, no UEP (SNP) loci, a sample size of 10 haplotypes

3 3 2 1 7 8 2 3 10 11
5 5 4 7 9 1 2 3 4 3
2 5 1 3 1 5 6 2 4 4
3 3 1 5 7 8 2 3 11 13
5 5 4 7 9 1 2 3 4 3
1 7 6 2 3 3 2 3 2 1
1 4 2 3 3 6 6 2 1 3
2 6 8 3 4 2 4 3 3 1
4 4 2 1 7 9 1 1 11 12
1 5 2 2 3 6 6 2 4 2

• Wilson, Weale & Balding 2003.Inferences from DNA data: population histories, evolutionary processes and forensic match probabilities. Journal of the Royal Statistical Society: Series A, 166: 155-188.