GSR: Simulator - Geonomics

Basic Package Attributes
AttributeValue
Title Geonomics
Short Description A Python package for simulation of genomic evolution on complex and dynamic landscapes
Long Description Geonomics is a Python package for forward-time, individual-based, continuous-space, population genomic simulations on complex and dynamic landscapes. Geonomics models are parameterized by way of an informatively annotated parameters file that provides the user a straightforward means of building models of arbitrary complexity while offering reasonable default settings and “off switches” for parameters and components unrelated to the user’s interests. Models consist of 1) a landscape with one or more environmental layers, each of which can undergo arbitrarily complex environmental change events and 2) one or more species having genomes with realistic architecture and any number of associated phenotypes. Species undergo non-Wright-Fisher evolution in continuous space, with localized mating and mortality, such that species-level phenomena and simulation dynamics are emergent properties of a model’s parameterization. Evolution is comprehensively tracked by way of tskit data structures that record the complete spatial pedigree, providing for the customizable output of rich, 3D data sets in a variety of common formats, including VCF and FASTA for genomic data, GeoTiff for landscape data, and CSV, Shapefile, and GeoJSON for individuals’ nongenomic data (location, environmental values, phenotypes, age, and sex). All of this allows Geonomics to produce realistic landscape genomic results useful for a wide variety of theoretical and empirical purposes.
Keywords landscape genomics, quantitative trait, multiple traits, environmental change, spatial simulation, agent-based simulation, population dynamics, life history, spatial pedigree, spatially varying selection, non-Wright-Fisher, Python, scripting, visualization
Version 1.3
Project Started 2019
Last Release 3 years, 8 months ago
Homepagehttps://github.com/erthward/geonomics
Citations Terasaki Hart DE, Bishop AP, Wang IJ, Geonomics: Forward-Time, Spatially Explicit, and Arbitrarily Complex Landscape Genomic Simulations., Mol Biol Evol, Sept. 27, 2021 [ Abstract, cited in PMC ]
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Last evaluatedMarch 8, 2022 (1138 days ago)
Author verificationThe basic description provided was derived from a website or publications by the GSR team and has not yet been verified by the simulation author. To modify this entry or add more information, propose changes to this simulator.
Detailed Attributes
Attribute CategoryAttribute
Target
Type of Simulated DataGenotype at Genetic Markers, Diploid DNA Sequence,
VariationsBiallelic Marker, Single Nucleotide Variation,
Simulation MethodForward-time,
Input
Data TypeAllele Frequencies, Other,
File formatOther,
Output
Data TypeGenotype or Sequence, Phenotypic Trait, Phylogenetic Tree, Demographic, Linkage Disequilibrium, Diversity Measures, Fitness,
Sequencing ReadsOther,
File FormatFasta or Fastq, VCF, Program Specific, Other,
Sample TypeRandom or Independent, Other,
Phenotype
Trait TypeQuantitative, Multiple,
DeterminantsSingle Genetic Marker, Multiple Genetic Markers,
Evolutionary Features
Demographic
Population Size ChangesConstant Size, Exponential Growth or Decline, Logistic Growth, Bottleneck, Carrying Capacity, User Defined,
Gene FlowInfluenced by Environmental Factors, Other,
SpatialityContinuous Models, Landscape Factors,
Life CycleDiscrete Generation Model, Age structured, Overlapping Generation,
Mating SystemRandom Mating, Polygamous, Age- or Stage-Specific, Other,
FecundityConstant Number, Randomly Distributed,
Natural Selection
DeterminantPhenotypic Trait, Environmental Factors,
ModelsDirectional Selection, Balancing Selection, Multi-locus models, Other,
RecombinationUniform, Varying Recombination Rates,
Mutation ModelsTwo-allele Mutation Model, Infinite-sites Model, Others,
Events AllowedVarying Demographic Features, Population Events, Other,
Other
InterfaceCommand-line, Script-based,
Development
Tested PlatformsMac OS X, Linux and Unix,
LanguagePython,
LicenseMIT,
GSR CertificationAccessibility, Documentation, Support,

Number of Primary Citations: 1

Number of Non-Primary Citations: 0

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