Forward-in-time simulation software tools | Population genetics data analysis
In population genetics, simulation is a fundamental tool for analyzing how basic evolutionary forces such as natural selection, recombination, and mutation shape the genetic landscape of a population. Forward simulation represents the most powerful, but, at the same time, most compute-intensive approach for simulating the genetic material of a population.
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.
A simulation tool that can simulate sequence data with user-specified disease and quantitative trait models. SeqSIMLA can efficiently simulate sequence data with disease or quantitative trait models specified by the user. It is useful for evaluating statistical properties for new study designs and new statistical methods using NGS.
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.
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.
Generates datasets using a forward-time population simulator which relies on random mating, genetic drift, recombination, and population growth to allow a population to naturally obtain linkage disequilibrium (LD) features. GenomeSIMLA was developed for the simulation of large-scale genomic data in population based case-control samples. GenomeSIMLA allows the user to specify many evolutionary parameters and control evolutionary processes.
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).
A forward-time population genetics simulation environment. The core of simuPOP is a scripting language (Python) that provides a large number of objects and functions to manipulate populations, and a mechanism to evolve populations forward in time. Using this R/Splus-like environment, users can create, manipulate and evolve populations interactively, or write a script and run it as a batch file.
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.
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.
A flexible forward evolutionary simulation tool for exploring the consequences of evolution by phenotype, whereby demographic, chance, behavioral and selective effects mold genetic architecture. Simulation is useful for exploring these issues as well as the choice of study design inferential methods.
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.
A simulation tool for the generation of haplotype data. The simulated haplotypes are such that their allele frequencies and linkage disequilibrium coefficients match exactly those estimated in a real sample.
A C++ and Python library to simulate large populations that are polymorphic at many loci. FFPopSim allows for complex fitness functions, including pairwise and higher order epistasis. It is designed to study the effects of linked selection, the rare processes in large populations, and can be used to address a large variety of population genetics problems.
Allows the simulation of evolution at the level of genes, gene families, and whole genomes. EvolSimulator was designed with the goal of investigating evolutionary phenomena like biased mutation regimes in different lineages, complicated patterns of selective pressure across sequences, and the confounding effects of paralogy and lateral genetic transfer.
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.
Allows modeling of very complex demographic scenarios. MetaPopGen removes the limitations imposed by large population size, which affect individual-based simulation models. It focuses on genotype numbers rather than on individuals. The tool is indicated to study large populations and very complex demographic scenarios and its capabilities were demonstrated by applying it to the case of a marine fish metapopulation in the Mediterranean Sea.
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.
Implements almost any arbitrary population-genetic and demographic model in a spatially explicit context using a variety of dispersal kernels. kernelPop implements biparental inheritance of unlinked diploid loci and maternal inheritance of haploid loci. Currently, loci are selectively neutral. Three mutation models are implemented: infinite allele model, strict stepwise model, and a simple 1-parameter model of DNA nucleotide substitution.
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.