hBayeSSC download available here: https://github.com/UH-Bioinformatics/hBayeSSC

hBayeSSC is a Python script that wraps around Serial SimCoal in order to simulate a multi-taxa community undergoing a coordinated demographic expansion.

**Requirements:**

The applications required to produce a set of simulations with multitaxa summary statistics for the hABC analysis described in Chan et al. 2014:

- BayeSSC - Serial Simcoal

- Python 2.x >= 2.4

- hBayeSSC.py

- msReject

**Input files**

The input files needed to produce a set of simulations with multitaxa summary statistics for the hABC analysis described in Chan et al. 2014:

- A table of observed summary statistics for each taxon in the community. (details)

- An input par file for serial simcoal. (details)

**Observation summary statistics:**

Sample observation file:

The table of observed summary statistics consists of columns with the following header names. hBayeSSC replaces the appropriate line in the par file with these values:

Column name = Description

species = Name of taxa

nsam = number of samples to be simulated

nsites = Number of base pairs

tstv = % transitions

gamma = Gamma shape parameter

gen = Numbers of years per generation

locuslow = Low estimate of the locus mutation rate per generation

locushigh = High estimate of the locus mutation rate per generation

Nelow = Low estimate for effective population size

Nehigh = High estimate for effective population size

SegSites = Segregating sites

nucdiv = Nucleotide diversity

Haptypes = Number of haplotypes

HapDiver = Haplotypic diversity

TajimasD = Tajima's D

F* = Fu's F

A more complete description of these values can be found on the BayeSSC website.

**par file**

**Sample .par file**

The par file contains one prior which is not individually replaced, such as expansion magnitude (under historical events) and will apply to all populations.

Then we use the following R-script and abc.R to do the final 1,000 acceptance and parameter estimation using local linear regression.

BayeSSC (Bayesian Serial SimCoal)
http://web.stanford.edu/group/hadlylab/ssc/