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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.
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.
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.
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).
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.
CDPOP / Cost Distance POPulations
A spatially-explicit simulator of gene-flow in complex landscapes to explain observed population responses and provide a foundation for landscape genetics. The program implements individual-based population modeling with Mendelian inheritance on a resistant landscape. Simulation begins with an initial homogeneous population and followed by divergence through time as functions of individual based movement, breeding and dispersal on a continuous cost surface.
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.
Allows the simulation of genetic and phenotypic data for complex quantitative traits in a realistic and dynamic metapopulation with selective pressures. quantiNemo was developed to investigate the effects of selection, mutation, recombination and drift on quantitative traits with varying architectures in structured populations connected by migration and located in a heterogeneous habitat. It consists of several simulation components, which may be easily extended and is built in the evolutionary and population genetics-programming framework NEMO.
Models dynamics of multiple populations and their interactions through individual based simulations while simultaneously recording genotype, pedigree, and trait information at the individual level. PEDAGOG allows for specification of heritable traits, natural and sexual selection acting upon those traits, population sampling schemes, and incorporation of genetic and demographic errors into the output. Parameters such as genetic diversity, demographics, mating design, genetic and demographic errors, individual growth models, trait heritability and selection, and output formatting can be specified. Simulation results can be automatically formatted for 57 existing software programs to facilitate post-simulation analysis.
A flexible, easy to use population genetic simulator that tracks the ancestry of the entire population in question. TreesimJ provides many fitness and demographic models and new models are easy to develop. Data collection is performed by a variety of independently configurable collectors which periodically sample the population and record statistics. TreesimJ allows researchers to easily sample and analyze gene genealogies and related data from populations evolving under a wide variety of selective and demographic regimes. It is likely to be useful for population genetic researchers seeking to understand the links between evolutionary and demographic forces, genealogical structure and the resulting patterns of genetic variation.
A Mac OS X software for performing spatially realistic simulations. MARLIN improves the workflow of performing population genetic simulations by providing user interface with realistic geographic scenarios to create, run, analyse, and visualize genetic simulations. It also uses a command line program QuantiNemo to run it. When simulations are finished, MARLIN directly analyses and plots the results, thereby greatly simplifying the simulation workflow. This combination of tasks makes MARLIN ideal for teaching and for scientists who are interested in doing simulations without having to learn command-line operations.
A plugin to perform individual-based population genetic simulations. rmetasim combines realistic demography, including temporal variation in vital rates, with neutral evolution at multilocus genotypes. A wide range of landscape-level dynamics, population structures, and within-population demographies can be represented using this software. Additionally, this software could be used to estimate the power of a particular technique in inferring demographic parameters under realistic conditions, and to provide an environment to compare alternative approaches to infer the same parameter.
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.
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.
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.
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.
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.
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.
SPIP / Simulate Pedigree In Population
Simulates multilocus genetic data on individuals in age-structured populations. SPIP allows investigation of the relationship between family structure and population parameters. The tool will be useful for evaluating multilocus estimators of pairwise relatedness and population structure, and for simulating the distribution of relatedness in populations with varying demographies. It provides a method for simulating genetic drift in complex populations.
Population Lab
Provides several models of familial disease aggregation and show that the parameters used in the simulations are faithfully estimated. Population Lab is a method and a software package for simulating realistic populations of related individuals, using easily available vital statistics (population counts and fertility and mortality rates). It can be used to investigate various underlying models of disease aggregation in families and enhance the development of optimal approaches for family studies.
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.
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.
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.
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.
SEEDY / Simulation of Evolutionary and Epidemiological DYnamics
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).
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.
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.
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