Detecting and measuring selection from gene frequency data
Current version

All changes since first version are described here.


The software package SelEstim is aimed at distinguishing neutral from selected polymorphisms and estimate the intensity of selection at the latter. The SelEstim model accounts explicitly for positive selection, and it is assumed that all marker loci in the dataset are responding to selection, to some extent. SelEstim is written in C. The source code as well as executables for various platforms (currently OS X, Windows, Linux) are available. The C executable reads a data file supplied by the user, and a number of options can be passed through the command line. The manual provides information about how to format the data file, how to specify the user-defined parameters, and how to interpret the results.

Developed by

If you have any question, please feel free to contact me. However, I strongly recommend you read the manual first.

Send a message


Vitalis R., Gautier M., Dawson K. J. and Beaumont M. A. 2014. Detecting and measuring selection from gene frequency data. Genetics 196: 799-817


KimTree is a free software under the the GPL licence and copyright © 2013 INRAE.

Last updated

By Renaud Vitalis on 2017-09-07