Skip to content

luntergroup/smcsmcScrm

 
 

Repository files navigation

This is the jz_stable branch Project Status: Active - The project has reached a stable, usable state and is being actively developed. Build Status Coverage Status

scrm

scrm simulates the evolution of genetic sequences. It takes a neutral evolutionary model as input, and generates random sequences that evolved under the model. As coalescent simulator, it traces the ancestry of the sampled sequences backwards in time and is therefore extremely efficient. Compared to other coalescent simulators, it can simulate chromosome-scale sequences without a measureable reduction of genetic linkage between different sites.

Installation

Stable Release (recommended)

You can download the latest stable release packaged for a variety of different platform from scrm's homepage. Instructions on building the binary from the source packages are available in the wiki.

Development Version From GitHub

You can also install scrm directly from the git repository. Here, you need to install autoconf first:

On Debian/Ubuntu based systems:

apt-get install build-essential autoconf autoconf-archive libcppunit-dev

On Mac OS:

port install automake autoconf autoconf-archive cppunit

Afterwards you can build the binary using

./bootstrap
make

Usage

We designed scrm to be compatible to the famous program ms from Richard R. Hudson. You can use it as a drop in replacement for ms if you avoid the options -c and -s. Details are available in the wiki.

Troubleshooting

If you encounter problems while using scrm, please file a bug report or mail to develop (at) paulstaab.de.

Citation

scrm is described in the manuscript

Paul R. Staab, Sha Zhu, Dirk Metzler and Gerton Lunter. scrm: efficiently simulating long sequences using the approximated coalescent with recombination. Bioinformatics (2015) 31 (10): 1680-1682. doi:10.1093/bioinformatics/btu861.

Licence

You can freely use all code in this project under the conditions of the GNU GPL Version 3 or later.

Packages

No packages published

Languages

  • C++ 49.0%
  • Jupyter Notebook 20.8%
  • Shell 19.8%
  • Python 5.6%
  • M4 2.5%
  • R 1.1%
  • Other 1.2%