Provides a gene tree estimation error method. Statistical binning is used in genome-scale species tree estimation with MP-EST, a coalescent-based species tree estimation method. This method produced a tree that was highly congruent with the concatenation analysis and was consistent with the prior scientific literature. It reduces the error in species tree topology and branch length estimation.

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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 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).

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.

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.

Allows estimation of population-genetic parameters. LAMARC is a genealogy-sampler software that can calculate the population sizes, population exponential growth rates, migration rates, and per-site recombination rate of n populations using DNA, single nucleotide polymorphism (SNP), microsatellite, or electrophoretic data. The software can also perform fine-scale linkage disequilibrium mapping, relating phenotypic data to genetic variation.

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.

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.

Predicts statistics and distribution of crossovers for (family) DNA shuffling under different experimental conditions (e.g., annealing temperature, fragmentation length, DNA concentration, salt concentration, etc.). eShuffle is a quantitative framework for assessing the number, type, and distribution of crossovers proposed in the context of DNA shuffling. Comparisons of predictions against experimental data reveals good agreement, particularly in light of the fact that there are no adjustable parameters. Therefore, no reparameterization is needed when experimental conditions or the sequences to be shuffled change, thus providing a versatile framework for comparing different protocol choices and setups.

A Monte Carlo computer program is available to generate samples drawn from a population evolving according to a Wright-Fisher neutral model. The program assumes an infinite-sites model of mutation, and allows recombination, gene conversion, symmetric migration among subpopulations, and a variety of demographic histories. The samples produced can be used to investigate the sampling properties of any sample statistic under these neutral models.

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).

Simulates coalescent simulation of intracodon recombination and of coding DNA sequences with recombination, migration and demography. Recodon allows to simulate samples of coding DNA sequences under complex scenarios, nucleotide and codon sequences from haploid/diploid populations with intra/inter codon recombination, migration, demographics and dated tips. It could be used to more realistically model the evolution of nuclear genes and fast-evolving pathogens or the estimation of genetic parameters using approximate Bayesian computation.

Provides three single-sample estimators and standard temporal method. NeEstimator is suitable for empirical and simulated datasets containing varying numbers of nuclear genotypes consisting of two or more loci and having two or more alleles per locus. It is able to account for missing data calculating a unique fixed-inverse variance-weighted harmonic mean. The tool provides confidence intervals for all methods and in several cases implements new and improved routines.

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.

Proposes a rapid coalescent-based approach to simulate whole genome data. In addition to features of standard coalescent simulators, the program allows for recombination rates to vary along the genome and for flexible population histories. The program can be used to study the sampling properties of any statistic for a whole genome study.

Both crossover and gene conversion hotspots have been incorporated into an existing coalescent-based program for simulating genetic variation data for a sample of chromosomes from a population.

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.

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 coalescent simulator for biological sequences. Different to similar programs, scrm can approximate the Ancestral Recombination Graph as closely as needed, but still has only linear runtime cost for long sequences. It allows you to rapidly simulate chromosome scale sequences with essentially correct genetic linkage.

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.

A program to simulate genetic diversity based on a realistic vectorized environment. AQUASPLATCHE starts by dividing a realistic vectorized network of river streams into segments of arbitrary length. The program then proceeds by simulating the colonization of the streams from an arbitrary source, recording the evolution of the segment densities and the migration events between adjacent segments over time. This demographic history is then used to generate genetic data of population samples located in various segments of the river system, using a backward coalescent framework.

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.

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.

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.

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).

An R package for calling coalescent simulators with a unified syntax. Coala can execute simulations with several programs, calculate additional summary statistics and combine multiple simulations to create biologically more realistic data. It allows researchers to conduct and process coalescent simulations in an easy, reliable and reproducible way. Different simulators can be called using a unified R syntax and a variety of summary statistics can be calculated from the results.

Displays the complex demographic information from simulation scripts or parameter files. POPdemog returns a demographic model. It can reduce the number of crossings of migration arrows and population branches. This tool enables the construction of figures that offer fine-scale representation of the overlapping migration events during multiple migrations.

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.

A simulator for the discrete time Wright-Fisher model (DTWF) process that scales up to hundreds of thousands of samples and whole-chromosome lengths, with a time/memory performance comparable or superior to currently available methods for coalescent simulation. ARGON supports arbitrary demographic history, migration, Newick tree output, variable mutation/recombination rates and gene conversion, and efficiently outputs pairwise identical-by-descent (IBD) sharing data.

Allows calculation of the state of any node in a phylogeny under the marginal approximation of the structured coalescent. MASCOT is a BEAST 2 package whose algorithm entirely avoids the sampling of migration histories. The software can infer migration rates and effective population sizes reliably, including when many different states are present. It was applied to a geographically distributed samples of human Influenza A/H3N2 virus for demonstrating its applicability to large datasets.

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.

Simulates the separation of mutation from selection and allows the user to set selection conditions. EvolveAGene simulates the evolution of intact coding sequences. It produces realistic data sets and should be a valuable tool for evaluating a variety of computational biology and phylogenetic programs. The tool does not permit designating a specific region of the sequence or specific codons as being highly conserved.

Allows likelihood analysis of genetic data. Migraine is a software which implements coalescent algorithms for maximum likelihood analysis of population genetic data, with a focus on the inference of dispersal for spatially structured populations and historical events for isolated panmictic populations. The method is based on importance sampling of gene genealogies, extended for new mutation models, notably the generalized stepwise mutation model (GSM).

Deduces the barcode gap from the data and to partition the data set using statistical methods. ABGD can be used to obtain the finest partition of a data set into candidate species. It was designed to automates the formulation of species hypotheses. This tool does not infer ancestral states. It can be applied to nuclear sequences that have experienced recombination.

Estimates the effective population sizes with coalescent approach using microsatellite markers. VarEff is a software which works on steps of constant size to resolve the probabilities by an approximation of maximum likelihood from a Bayesian posterior distribution. The estimation is done on simulated demographic histories modelled by steps of constant size for which the posterior probabilities are derived using an approximation of likelihood.

Provides an evolution of msPar, the parallel version of the coalescent simulation program ms, which removes the limitation for simulating long stretches of DNA sequences with large recombination rates, without compromising the accuracy of the standard coalescence. msParSm achieves high parallel efficiency figures (>70%) when working with large recombination rate.

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.

Computes the likelihood with data on multiallelic markers. MCLEEPS uses an importance sampling method to compute the likelihood for the population genetics parameter Ne, given data on temporal changes of allele frequencies in a population. The forward-backward method here, and variations of it, is useful in estimating population parameters from such models using Monte Carlo likelihood.

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.

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 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.

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.

Allows to study colonization of a new ecological niche. symsim consists in a generations model, and each generation represents a population growth, resource competition, and recombination in a sympatric pool. It can model a microbial population growing in an environment composed of two distinct niches, one ancestral and one derived. This tool is useful to investigating the colonization of a new niche.

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.

A tool for simulating the coalescent process with recombination and gene conversion under various demographic models. CoaSim effectively constructs the ancestral recombination graph for a given number of individuals and uses this to simulate samples of SNP, micro-satellite, and other haplotypes/genotypes. The generated sample can afterwards be separated in cases and controls, depending on states of selected individual markers. The tool can accordingly also be used to construct cases and control data sets for association studies.

Concerns generating uniform random permutations of biological sequences (such as DNAs, RNAs, and proteins) that preserve the exact k-let counts. The uShuffle tool implements the latest variant of the Euler algorithm and uses Wilson's algorithm in the crucial step of arborescence generation. It achieves flexibility by allowing arbitrary alphabet size and let size, and is available in many forms for different kinds of users.

Generates samples of DNA sequences when there is a biallelic site targeted by selection. The mbs software is so flexible that it can incorporate any arbitrary histories of population size changes and any mode of selection as long as selection is operating on a biallelic site. This provides opportunities to investigate the effect of any mode of selection on the pattern of single nucleotide polymorphisms (SNPs) under various demography.

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.

Facilitates the estimation and description of recombination in population genomics and evolutionary biology. SC is a method of modeling coalescence with recombination which considerably improved the algorithm described by Wiuf and Hein. This algorithm constructs ancestral recombination graphs (ARG) spatially along the sequence, but it does not produce any redundant branches which are inevitable in Wiuf and Hein’s algorithm. Interestingly, the distribution of ARG generated by the present algorithm is identical to that generated by a typical back-in-time model adopted by ms, an algorithm commonly used to model coalescence. It is here demonstrated that the existing approximate methods such as the sequentially Markov coalescent, a related method called SMC′, and Markovian coalescent simulator (MaCS) can be viewed as special cases of the present method.

Simulates large chromosomal regions, such as those appropriate in a consideration of genome-wide data, in a way that is several orders of magnitude faster than existing coalescent algorithms. FastCoal provides a useful resource for those needing to simulate large quantities of data for chromosomal-length regions using an approach that is much more efficient than traditional coalescent models.

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