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Analyzes comparative DNA sequence data. SITES is a computer program primarily intended for data sets with multiple closely related sequences. It is especially useful when multiple sequences have been obtained from each of one or several closely related populations or species. Basic analyses include: data summaries by polymorphism class; polymorphism estimates within and between groups (species); estimates of migration, neutral model, and recombination parameters; and linkage disequilibrium analyses.


Facilitates joint Bayesian inference of ancestral recombination graphs (ARG) and related parameters from bacterial sequence alignments under the ClonalOrigin model. Bacter is a BEAST 2 package which allows to infer the ancestral recombination graph (ARG) that gave rise to sampled data, including both clonal frame and the recombinant edges. For informative data sets, it can sample posterior distributions for parameters such as the recombination rate and expected converted tract length jointly with the ARG.

Infusion / Inference Using Simulation

Implements functions for simulation-based inference. Infusion is a software which is aimed to construct an estimation of likelihood surfaces for summary statistics, from which likelihood ratio confidence intervals can be constructed. The software handles models with less than nine parameters. It is based on two main sets of techniques: the modelling of empirical distributions of summary statistics using mixtures of Gaussian distribution and the inference of likelihood surfaces from estimates of the likelihood of given parameter points.


Provides an implementation of Hudson’s algorithm. msprime provides an ms compatible command line interface along with a Python API. This implementation uses a simple linked-list based representation of ancestral segments, and uses a binary indexed tree to ensure the choice of ancestral segment involved in a recombination event can be done in logarithmic time. The implementation of msprime is based on the listings for Hudson’s algorithm, which should provide sufficient detail to make implementation in a variety of languages routine.


Facilitates phylodynamic inference and analysis based on gene genealogies. phylodyn’s main functionality is Bayesian nonparametric estimation of effective population size fluctuations over time. The implementation includes several Markov chain Monte Carlo (MCMC)-based methods and an integrated nested Laplace approximation-based approach for phylodynamic inference. In phylodyn, individuals are assumed to be sampled at the same point in time (isochronous sampling) or at different points in time (heterochronous sampling). In addition, sampling events can be modelled with preferential sampling, which means that the intensity of sampling events is allowed to depend on the effective population size trajectory.


Models bacterial recombination. FastSimBac is a simulation software that includes the bacterial sequential Markov coalescent (BSMC) model. The software also includes additional event types: mutation, migration, speciation, demographic change, recombination hotspots, and between species recombination. It allows specification of the clonal frame upon which simulations can be conditioned, which may grant simulations a closer fit to particular datasets when the clonal frame is readily estimable.

SPLATCHE / SPatiaL And Temporal Coalescences in Heterogeneous Environments

Simulates complex and realistic demographic models and to generate the associated molecular diversity of sampled individuals. Alternative population or environmental histories can be modelled and compared through their impacts on resulting genetic diversity. Due to its explicit handling of spatial information and of environmental and temporal heterogeneities, SPLATCHE2 is particularly well suited for studying spatially distributed population samples over relatively short evolutionary time scales (i.e. a few thousand generations).


Predicts the genetic diversity at a microsatellite DNA marker, in a finite population, for various mutation models and for variable population size. DemoDivMS is aimed to describe the expected current genetic diversity at a microsatellite marker from the past history of a population. The software estimates the final genetic diversity using coalescent theory adapted to variable effective size. Calculations are based on the joint analysis of the drift process in a finite population and of the mutation process at a microsatellite marker.

SimRA / Simulation based on Random graph Algorithms

Simulates generic multiple population evolution model with admixture. It is based on random graphs that improve dramatically in time and space requirements of the classical algorithm of single populations. Using the underlying random graphs model, we also derive closed forms of expected values of the ancestral recombinations graph characteristics i.e., height of the graph, number of recombinations, number of mutations and population diversity in terms of its defining parameters. This is crucial in aiding the user to specify meaningful parameters for the complex scenario simulations, not through trial-and-error based on raw compute power but intelligent parameter estimation.


An efficient simulator that supports both exact and approximate coalescent simulation with positive selection. cosi2 improves on the speed of existing exact simulators, and permits further speedup in approximate mode while retaining support for selection. cosi2 supports a wide range of demographic scenarios, including recombination hot spots, gene conversion, population size changes, population structure and migration. cosi2 implements coalescent machinery efficiently by tracking only a small subset of the Ancestral Recombination Graph, sampling only relevant recombination events, and using augmented skip lists to represent tracked genetic segments.


Simulates complex traits involving quantitative and/or fitness components. Geno-Diver is a combined coalescence and forward-in-time simulator that implements multiple selection and mating strategies utilizing pedigree or genomic information. The software can simulate both trait categories along with a covariance between them. It can provide a platform to facilitate fundamental research on how to maximize the fitness of livestock populations while increasing yield and efficiency traits.


A C++ library of routines intended to facilitate the development of forward-time simulations under arbitrary mutation and fitness models. The library design provides a combination of speed, low memory overhead, and modeling flexibility not currently available from other forward simulation tools. The library is particularly useful when the simulation of large populations is required, as programs implemented using the library are much more efficient than other available forward simulation programs.

BaySICS / Bayesian Statistical Inference of Coalescent Simulations

Performs Approximate Bayesian computation (ABC) analyses by means of coalescent simulations from DNA sequence data. BaySICS estimates historical demographic population parameters and performs hypothesis testing by means of Bayes factors obtained from model comparisons. Although providing specific features that improve inference from datasets with heterochronous data, BaySICS also has several capabilities making it a suitable tool for analysing contemporary genetic datasets. Those capabilities include joint analysis of independent tables, a graphical interface and the implementation of Markov-chain Monte Carlo (MCMC) without likelihoods.

IRiS / Identification of Recombinations in Sequences

Detects high confidence recombination events in their shared genealogy. IRiS assigns an estimated age to each internal node of G. It uses a model-based approach to detecting recombinations in H. The tool constructs the ARG from the haplotype data in two phases. In the first phase it detects the recombinations and only the ones with high confidence are used in the next phase. In the second phase these recombinations, along with local topology information, are reconciled into an ARG network.


A coalescent simulation program for a structured population with selection at a single diploid locus. MSMS includes the functionality of the simulator ms to model population structure and demography, but adds a model for deme- and time-dependent selection using forward simulations. The program can be used, e.g. to study hard and soft selective sweeps in structured populations or the genetic footprint of local adaptation. The implementation is designed to be easily extendable and widely deployable.

MaCS / Markovian Coalescent Simulator

forum (1)
Simulates geneologies spatially across chromosomes as a Markovian process. MaCS can efficiently simulate haplotypes under any arbitrary model of population history. MaCS produces simulated data that are virtually identical to data simulated under the standard coalescent, but in much less time and using much less memory. MaCS can be used in an applied context to simulate genome-wide case-control data under any specific disease model.


Simulates genotypic data under general isolation by distance models. IBDSim can consider a large panel of subdivided population models representing discrete subpopulations as well as a large continuous population. Many dispersal distributions, with different tails, can be considered as well as various heterogeneities in space and time of the demographic parameters. IBDSim can simulate allelic and sequence data under various mutation models (IAM, KAM, SMM, GSM, ISM, JC69, K2P, F81, HKY, TN, SNP), continuous temporal changes in density and habitat sizes, simple barriers to gene flow and pre and post dispersal sampling. It also includes a graphical interface.


A method for simulating samples of marker haplotypes, genotypes, or diplotypes in case-control studies in which the markers are linked to a disease locus in any specified region of the genome. The method allows realistic features to be incorporated into the simulations, including selection acting on disease alleles, sample ascertainment of disease chromosomes and polymorphic markers, a genetic dominance model of disease expression that allows incomplete penetrance and phenocopies, and an accurate genetic map of recombination rates and hotspots for recombination in the human genome (or, alternatively, an improved method for simulating the distribution of hotspots).


A coalescent-based simulation program which is able to quickly simulate a variety of genetic markers scattered over very long genomic regions with arbitrary recombination patterns under complex evolutionary scenarios. 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.


Can simulate arbitrarily complex patterns of rate variation and multiple indel processes, and allows the incorporation of selective constraints on indel events. PhyloSim is an extensible framework for the Monte Carlo simulation of sequence evolution using the Gillespie algorithm to integrate the actions of many concurrent processes such as substitutions, insertions and deletions (indels). PhyloSim significantly extends the range of realistic evolutionary patterns that can be simulated, and is freely extensible within the R environment.

GONe / Generational Overlap Ne

Uses the Jorde-Ryman modification to the temporal method to account for age-structure in populations. GONe is a user-friendly, Windows-based program for estimating effective size (Ne) in populations with overlapping generations. This method requires estimates of age-specific survival and birth rate, and allele frequencies measured in two or more cohorts spaced any number of generations apart. GONe has been validated over a wide range of Ne values, and for scenarios where survival and birth rates differ between sexes, sex-ratios are unequal, and reproductive variances differ.


Detects recent effective population size reductions from allele data frequencies. BOTTLENECK computes for each population sample and for each locus the distribution of the heterozygosity expected from the observed number of alleles (k), given the sample size (n) under the assumption of mutation-drift equilibrium. This distribution is obtained through simulating the coalescent process of n genes under three possible mutation models, the Infinite Allele Model (IAM), Stepwise Mutation Model (SMM) and the two phase model (TPM).


Allows for simulation of the genomic diversity of samples drawn from a set of populations with arbitrary patterns of migrations and complex demographic histories, including bottlenecks and various modes of demographic expansion. The main additions to the previous version include the possibility of arbitrary and heterogeneous recombination rates between adjacent loci and multiple coalescent events per generation, allowing for the simulation of very large samples and recombining genomic regions, together with the simulation of single nucleotide polymorphism data with frequency ascertainment bias.

GFMCMC / GLUT for Markov Chain Monte Carlo

Provides a system for visualizing the variables involved in Markov chain Monte Carlo (MCMC). GFMCMC is designed to provide a relatively simple user interface that allows management of multiple windows which provide different views of the variables involved in simulation. It is written in C/C++. The window management system uses calls to Mark Kilgaard’s OpenGL Utility Toolkit (GLUT). GLUT is almost platform independent, so the features of GFMCMC should work in almost the same way across different platforms.


Computes exact tests or their unbiased estimation for Hardy-Weinberg equilibrium, population differentiation, and two-locus genotypic disequilibrium. Genepop performs analyses of isolation by distance from pairwise comparisons of individuals or population samples, including confidence intervals for neighbourhood size. It allows comparison of differentiation over a given range of geographical distances, in intra vs. inter-ecotypic analyses thank to the implementation of a bootstrap analysis of mean differentiation.


Simulates haplotypes and single nucleotide polymorphims (SNPs) under a modified coalescent with recombination. SNPsim allows for the specification of non-homogeneous recombination rates, which results in the formation of the so-called ‘haplotype blocks’ of the human genome. The program also implements different mutation models and flexible demographic histories. This computational tool should prove very useful to the study of the statistical properties of haplotype blocks and their relevance in understanding of the human genome.

SNE / Serial NetEvolve

Generates DNA sequences evolved along a tree or recombinant network. Serial NetEvolve is a modification of the Treevolve program with the following additional features: simulation of serially-sampled data, the choice of either a clock-like or a variable rate model of sequence evolution, sampling from the internal nodes and the output of the randomly generated tree or network. Serial NetEvolve differs from the majority of simulation methods in that it incorporates both serial sampling and recombination along with additional features (heterogeneous evolution rate, sampling of internal nodes), while at the same time, maintaining the population parameters from Treevolve (migration rate, population growth rate, among others).

GENIE / GENealogy Interval Explorer

A framework for inferring the demographic function from reconstructed phylogenies. GENIE uses two approaches: demographic models and skyline plot. It infers demographic history from estimated phylogenies, and is best suited to data sets containing much phylogenetic information and is complementary to other packages that do incorporate phylogenetic error. If it’s primarily used for highly variable viral gene sequences, other types of sequence data with a significant amount of phylogenetic information can be taken.