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SBVB / Sequence-Based Virtual Breeding

Simulates complex traits and genotype data. SBVB is a sequence based population simulator that generates molecular and phenotypic data using real sequence data. The software allows users to specify any number of traits with their own quantitative trait loci (QTNs) and allelic effects can be specified. It can quickly access any set of single nucleotide polymorphism (SNP) genotypes, allowing users to compare the performance of different genotyping strategies in the same run.

SFS_CODE / Simulating Finite Sites under COmplex Demographic Events

Generates samples from populations with complex demographic histories under various models of natural selection. SFS_CODE performs simulations under a general Wright-Fisher model with arbitrary demographic, selective, and mutational effects. It allows the user to simulate realistic genomic regions with several loci evolving according to a variety of mutation models (from simple to context-dependent), and takes into account insertions and deletions. Each locus can be annotated as either coding or non-coding, sex-linked or autosomal, selected or neutral, and have an arbitrary linkage structure.

GeneEvolve

A simulator to handle life history scenarios and to generate individual-level phenotypes and realistic whole-genome sequence for large populations. GeneEvolve runs forward-in-time, which allows it to provide a wide range of scenarios for mating systems, selection, population size and structure, migration, recombination, and environmental effects. GeneEvolve can simulate multiple causes of environmental and genetic influences across a wide range of mating, selection, and life history scenarios, and it can track and extract the true identity by descent information between all pairs of individuals in the simulated population.

SeDuS / Segmental Duplication Simulator

A flexible and user-friendly forward-in-time simulator of patterns of molecular evolution within segmental duplications undergoing interlocus gene conversion and crossover. SeDuS introduces known features of interlocus gene conversion such as biased directionality and dependence on local sequence identity. Additionally, it includes aspects such as different selective pressures acting upon copy number and flexible crossover distributions. A graphical user interface allows fast fine-tuning of relevant parameters and straightforward real-time analysis of the evolution of duplicates.

PReFerSim

A C program that performs forward simulations under the Poisson Random Field (PRF) model. PReFerSim models changes in population size, arbitrary amounts of inbreeding, dominance, and distributions of selective effects. Users can track summaries of genetic variation over time and output trajectories of selected alleles. Trajectories from PreFerSim can be conditioned to have any present-day frequency desired by the user. Such simulations can be used to estimate the ages of selected alleles and/or strength of selection, to estimate the rate of selective sweeps, or to distinguish between hard and soft selective sweeps.

Admix'em

A forward-time simulator that allows for rapid and realistic simulations of admixed populations with selection. Complex selection can be achieved through user-defined fitness and mating-preference probability functions. Users can specify realistic genomic landscapes and model neutral SNPs in addition to sites under selection. Admix'em is designed to simulate selection in admixed populations but can also be used as a general population simulator. Admix’em makes the following assumptions: 1) nonoverlapping generations; 2) diploid sexual individuals; 3) only one sex (assumed to be female) exerts sexual selection.

INDELible

Provides a flexible and powerful tool for simulating molecular sequence evolution. INDELible is a portable and flexible application for generating nucleotide, amino acid and codon sequence data by simulating insertions and deletions (indels) as well as substitutions. Indels are simulated under several models of indel-length distribution. The program implements a rich repertoire of substitution models, including the general unrestricted model and nonstationary nonhomogeneous models of nucleotide substitution, mixture, and partition models that account for heterogeneity among sites, and codon models that allow the nonsynonymous/synonymous substitution rate ratio to vary among sites and branches.

disease sims

Explores the impact of genetic model and population growth on distribution of genetic variance across the allele frequency spectrum underlying risk for a complex disease. disease_sims, using forward-in-time population genetic simulations, shows that the genetic model has important impacts on the composition of variation for complex disease risk in a population. It simulates genome-wide association studies (GWAS) and performs heritability estimation on population samples. A particular model of gene-based partial recessivity, based on allelic non-complementation, aligns well with empirical results. This model is congruent with the dominance variance estimates from both single nucleotide polymorphisms (SNPs) and twins, and the minor allele frequency distribution of GWAS hits.

Nemo

Provides developers with abstract models allowing them to implement their own life-history traits and life-cycle events. Nemo is an individual-based, genetically explicit and stochastic population computer program for the simulation of population genetics and life-history trait evolution in a metapopulation context. It offers a large panel of population models, from the Island model to lattice models with demographic or environmental stochasticity and a variety of already implemented traits (deleterious mutations, neutral markers and more), life-cycle events (mating, dispersal, aging, selection, etc.) and output operators for saving data and statistics.

OncoSimulR

Addresses a wide range of questions that span from the effect of mutator/antimutator genes, to the interplay between fitness landscapes, population sizes and mutation rates. OncoSimulR implements forward-in-time genetic simulations of diallelic loci in asexual populations with special focus on cancer progression. Fitness can be defined as an arbitrary function of genetic interactions between multiple genes or modules of genes, including epistasis, restrictions in the order of accumulation of mutations, and order effects. Mutation rates can be made to differ between genes, and can be affected by (anti)mutator genes.

Discoal

Generates population samples that include selective sweeps in a feature-rich, flexible manner. discoal can perform simulations conditioning on the fixation of an allele due to drift or either hard or soft sweeps—even those occurring a large genetic distance away from the simulated locus. discoal can simulate sweeps with recurrent mutation to the adaptive allele, recombination, and gene conversion, under non-equilibrium demographic histories and without specifying an allele frequency trajectory in advance.

Geno-Diver

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.

SLiM

Combines putative dependency structures in a weighted manner, allowing for numerical optimization of dependency structure and model parameters simultaneously. Slim is a general-purpose forward genetic simulation framework that combines an engine for forward population genetic simulations with a high degree of flexibility in specifying complex evolutionary scenarios. It includes a graphical user interface (GUI) for simulation construction, interactive runtime control, and dynamic visualization of simulation output, facilitating easy and fast model development with quick prototyping and visual debugging.

fwdpp

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.

AnA-FiTS / Ancestry-Aware Forward-in-Time Simulator

Simulates genetic sequences of a population forward in time under a Fisher-Wright model with selection and dynamically changing population size. The two main aspects of AnA-FiTS are: an implementation of non-neutral forward simulation and ancestry-based simulation of neutral mutations. It data structure is based on references/pointers to mutation object instances. Also, this tool generates a graph structure that depicts the complete observable history of neutral mutations.

SimAdapt

Represents evolutionary processes of adaptation and population dynamics in changing landscapes, using the NetLogo environment. SimAdapt simulates the evolution of both neutral and adaptive genotypes of diploid, sexually reproducing individuals introduced in a landscape. It accounts for the transmission of genes according to Mendelian inheritance laws, dispersal and adaptation to local conditions. SimAdapt allows the integration of complex patterns including spatially and temporally explicit landscapes described at an accurate level.

Pydigree

Offers a user-friendly environment to develop genetic software. Pydigree allows users to create and manipulate genetic data. It provides functions for the simulation of both pedigrees and population-based datasets by a forward-time strategy. The user can specify acceptable rates of genotyping errors and genotype missingness. This tool is based on a standard Hidden Markov model (HMM). It is able to perform kinship and inbreeding coefficient calculation, variance component estimation and forward time simulation of pedigree datasets.

Bacmeta

Allows users to provide simulations about evolution of bacterial genomes in multiple connected populations. Bacmeta permits to modelize multiple arbitrarily connected populations for which the genome sequences are subjected to evolutionary events over discrete non-overlapping generations. The software can also be potentially applied in testing methods for inferring recombination or likelihood-free inference for model parameters based on the Approximate Bayesian Computation inference framework.

FractalSIM

Mimics various population genetics models. FractalSIM is a multi-scenario genome-wide simulation framework that accounts for natural selection pre-and post-admixture processes. It offers users the option to simulate various scenarios of population bottlenecks, complex admixture, selection and disease models. It also has advantages over existing tools: (i) it integrates several genetics simulation models into one framework and (ii) it has the ability to simulate genome-wide data.

SpartaABC

Implements an approximate Bayesian-computation rejection algorithm to infer indel parameters from sequence data. SpartaABC is a web app that extracts a vector of summary statistics from its input; it then performs repeated simulations using an integrated sequence simulator under various indel parameters. As part of a broader web service, it provides (i) MSA reconstruction (optional), (ii) tree reconstruction (optional), (iii) inference of indel dynamics and (iv) sequence simulation based on the inferred indel parameters (optional).

popRange

Provides a simulation framework for modeling highly probabilistic spatial and temporal population dynamics. Features such as spatially and temporally variable selection coefficients and demography are incorporated in a highly flexible manner. popRange is presented with an example simulation exploring a selected allele’s trajectory in multiple subpopulations. Researchers can use popRange to evaluate and test complex scenarios by simulating large-scale data with complicated demographic and selective features.

SEEDY / Simulation of Evolutionary and Epidemiological DYnamics

New
Contains functions for the simulation, visualization and analysis of bacterial evolution within and between-host. SEEDY implements stochastic models for the accumulation of mutations within hosts, as well as individual-level disease transmission. Genomic data can be simulated according to a variety of sampling strategies, with the option of sampling single genomes, or deep-sequence observations. Moreover, the package contains functions to describe the theoretical distribution of genetic distances between samples taken during a disease outbreak, under a range of assumptions.

PaGELL / Parametric Genetic Evaluation of Lifespan in Livestock

Analyzes (right-censored) longevity data in livestock populations, with a special emphasis on the genetic evaluation of breeding stock. PaGELL relies on a parametric generalization of the proportional hazard model; more specifically, the baseline hazard function follows a Weibull process and flexibility is gained by including an additional time-dependent effect with the number of change points defined by users. PaGELL can accommodate 3 different sources of variation (i.e., systematic, permanent environmental, and additive genetic effects) and both fixed and time-dependent patterns (only for systematic and permanent environmental effects).

GENS / Gene-Environment iNteraction Simulator

Simulates interactions among two genetic and one environmental factor. GENS allows for epistatic interactions. It is based on data with realistic patterns of linkage disequilibrium, and imposes no limitations either on the number of individuals to be simulated or on number of non-predisposing genetic/environmental factors to be considered. The tool provides large biologically realistic data sets with known features that can be used to challenge, and eventually improve, the statistical tools that are designed to identify those interactions.

Pyvolve

An open-source Python module for simulating sequences along a phylogenetic tree. Pyvolve simulates sequences along a phylogeny using continuous-time Markov models of sequence evolution for nucleotides, amino acids, and codons, according to standard approaches. The primary purpose of Pyvolve is to provide a user-friendly and flexible sequence simulation platform that can easily be integrated into Python bioinformatics pipelines without necessitating the use of third-party software.

SMARTPOP / Simulating Mating Alliance as a Reproductive Tactic for Populations

Facilitates large-scale statistical inference on interactions between social factors, such as mating systems, and population genetic diversity. SMARTPOP can simulate a wide range of genetic systems (autosomal, X-linked, Y chromosomal and mitochondrial DNA) under a range of mating systems and demographic models. It is designed to enable resource-intensive statistical inference tasks, such as Approximate Bayesian Computation. This tool allows quantitative analyses to address complex socio-ecological questions.

EpiSIM / Epistasis SIMulator

A software tool that can simulate some of the statistical properties of genetic data. EpiSIM is capable of expanding the range of the epistasis models that current simulators offer, including epistasis models that display marginal effects and those that display no marginal effects. One or more of these epistasis models can be embedded simultaneously into a single simulation data set, jointly determining the phenotype. In addition, epiSIM is independent of any outside data source in generating linkage disequilibrium patterns and haplotype blocks.