visits since March 2011
SIB fastsimcoal2
University of Berne

fast sequential Markov coalescent simulation of genomic data under complex evolutionary models

While preserving all the simulation flexibility of simcoal2, fastsimcoal is now implemented under a faster continous-time sequential Markovian coalescent approximation, allowing it to efficiently generate genetic diversity for different types of markers along large genomic regions, for both present or ancient samples. It includes a parameter sampler allowing its integration into Bayesian or likelihood parameter estimation procedure.

fastsimcoal can handle very complex evolutionary scenarios including an arbitrary migration matrix between samples, historical events allowing for population resize, population fusion and fission, admixture events, changes in migration matrix, or changes in population growth rates. The time of sampling can be specified independently for each sample, allowing for serial sampling in the same or in different populations.

Different markers, such as DNA sequences, SNP, STR (microsatellite) or multi-locus allelic data can be generated under a variety of mutation models (e.g. finite- and infinite-site models for DNA sequences, stepwise or generalized stepwise mutation model for STRs data, infinite-allele model for standard multi-allelic data).

fastsimcoal can simulate data in genomic regions with arbitrary recombination rates, thus allowing for recombination hotspots of different intensities at any position. fastsimcoal implements a new approximation to the ancestral recombination graph in the form of sequential Markov coalescent allowing it to very quickly generate genetic diversity for >100 Mb genomic segments.

fastsimcoal2 now allows one to estimate demographic parameters from the (joint) site frequency spectrum (SFS) using simulations to compute the expected SFS and a robust method for the maximization of the composite likelihood.

new version of fastsimcoal2 : fsc2603 (October 14th 2017 release - fixes a bug in ver

downloads (fsc26)

[windows logo]
Windows 64 bits
[linux logo]
Linux 64 bits
MacOSX Sierra (10.12-)

what's new in fastsimcoal26

New features

  1. Simple implementation of individual inbreeding
    • The average inbreeding coefficient of individuals in a population can now be specified as a third optional parameter in the sample size definition. In this case, the sample age needs to be defined (set to zero in most applications), as:
      <sample size> <sample age> <inbreeding coefficient>
  2. Possibility to define initial parameter values for demographic inference
    • Option -initvalues file.pv , where file.pv lists initial non-complex parameter values to use. This option is mainly useful when computing bootstrap confidence intervals, as it allows one to use less replicates for each bootstrap data set. A *.pv file is now automatically generated after each parameter estimation by fsc26
  3. Computation of MAF 1D and 2D SFS with option --foldedSFS by simply folding the corresponding unfolded SFS (for compatibility with angsd, where the minor allele is computed separately for each SFS)
  4. Optional faster but approximate log computations with option --logprecision n, where n is a number between 10 and 23 specifying the precision of the computation of logarithms. 23 means full precision and is the default value.
  5. Optional parameter optimization without taking singletons into account specified with option --nosingleton
  6. Syntax changes
    • For parameter optimization,
    • -N option has been suppressed, and maximum no. of iteration is now equal to that set by the -n option
    • The number of cycles to performed is now fixed and only specified with option -L
    • The -l option is now optional and means something different. It is now used to specify the number of cycles where information on monomorphic sites is used. After these initial cycles, likelihood will only be computed (and optimized) on the polymorphic sites. This option needs to be used together with the “reference” keyword in the .est file (see section on est file).
    • The –M option is now just a flag mentioning we want to perform parameter estimation from the observed SFS. It should therefore not be followed by any number.
    • Removed -D option to produce output in dadi format.
  7. Implementation of instantaneous bottlenecks with keyword instbot added to historical event definition. Only works in absence of recombination for the moment.
  8. No more warnings if deme size tends to zero or infinity if deme is empty (intoduced in ver

Bug corrections

See this page for a complete list of changes since first fastsimcoal release


Comparisons with other coalescent simulations programs such as ms, simcoal2 or MaCS can be found here

getting started

A quick overview of how to get started with fastsimcoal can be found here (but it is better to read the manual first)

visualizing scenarios modeld in par files

With Vitor Sousa, we have written an R script called ParFileInterpreter-v6.3.1.r that reads par files and plots the modeled scenario, which can be useful to check that the your modeled scenario corresponds to what you had in mind.  It can also be useful to visualize the scenario obtained after some parameter estimation (use the *_maxL.par file). More information on the use of the this program can be found here.

running fsc26 on a mac

I have realized (thanks to Melissa Wilson Sayre) that the plain version of fsc26 will not run on mac osX unless you have installed a recent version of gcc.

This is because fsc26 is multithreaded and it uses intel's libraries based on openMP, which are not distributed anymore with recent versions of mac OSX.

So to be able to run fsc26 on your mac, you need to first install a recent version of gcc.

To do so, follow these steps:
  1. Download gcc-7.1-bin.tar.gz
  2. Open a terminal
  3. cd to the download folder
  4. Extract the tar archive with the command 
    gunzip gcc-7.1-bin.tar.gz
  5. Install gcc ver 5.1 in /usr/local with the command
    sudo tar -xvf gcc-7.1-bin.tar -C /.

problems running fsc26 on linux (kernel too old)

It seems that fsc26 is not able to run on old linux version with an old kernel, potentially due to the need of openmp libraries that need to be dynamically linked to the program.

bug reports

Send an email to Laurent Excoffier or use the Google group list

discussion list

A Google group on fastsimcoal (!forum/fastsimcoal) has been created to promote discussion or allow queries on any aspect of fastsimcoal. Please use it!


fastsimcoal2 and higher:
Excoffier, L., Dupanloup, I., Huerta-Sánchez, E., Sousa, V.C., and M. Foll (2013) Robust demographic inference from genomic and SNP data. PLOS Genetics, 9(10):e1003905.

Excoffier, L. and Foll, M (2011) fastsimcoal: a continuous-time coalescent simulator of genomic diversity under arbitrarily complex evolutionary scenarios Bioinformatics 27: 1332-1334.

Last updated by L. Excoffier on 09.10.2017
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