SFS_CODE: More Efficient and Flexible Forward Simulations

Abstract

SUMMARYModern implementations of forward population genetic simulations are efficient and flexible, enabling the exploration of complex models that may otherwise be intractable. Here we describe an updated version of SFS_CODE, which has increased efficiency and includes many novel features. Among these features is an arbitrary model of dominance, the ability to simulate partial and soft selective sweeps, as well as track the trajectories of mutations and/or ancestries across multiple populations under complex models that are not possible under a coalescent framework. We also release sfs_coder, a Python wrapper to SFS_CODE allowing the user to easily generate command lines for common models of demography, selection, and human genome structure, as well as parse and simulate phenotypes from SFS_CODE output.\n\nAvailability and ImplementationOur open source software is written in C and Python, and are available under the GNU General Public License at http://sfscode.sourceforge.net.\n\nContactryan.hernandez@ucsf.edu\n\nSupplementary informationDetailed usage information is available from the project website at http://sfscode.sourceforge.net.