GSR: Editing - fastsimcoal2 Simulator

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Long Description (required)

While preserving all the simulation flexibility of simcoal2, fastsimcoal is now implemented under a faster continous-time sequential Markovian coalescent approximation, allowing it to efficiently generate genetic diversity for different types of markers along large genomic regions, for both present or ancient samples. It includes a parameter sampler allowing its integration into Bayesian or likelihood parameter estimation procedure.

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.

Different markers, such as DNA sequences, SNPs, STRs (microsatellites) or multi-locus allelic data can be generated under a variety of mutation models (e.g. finite- and infinite-site models for DNA sequences, stepwise or generalized stepwise mutation model for STRs data, infinite-allele model for standard multi-allelic data).

fastsimcoal can simulate data in genomic regions with arbitrary recombination rates, thus allowing for recombination hotspots of different intensities at any position. fastsimcoal implements a new approximation to the ancestral recombination graph in the form of sequential Markov coalescent allowing it to very quickly generate genetic diversity for >100 Mb genomic segments.

fastsimcoal2 now allows one to estimate demographic parameters from the (joint) site frequency spectrum (SFS) using simulations to compute the expected SFS and a robust method for the maximization of the composite likelihood.

Attribute Tree Control

Step 1: Use the attribute tree to add new attributes or remove pre-selected attributes to describe the simulator.

Every sub-attribute is selected
Not all sub-attributes are selected

Attributes

Target
- Type of Simulated Data
  - Genotype at Genetic Markers
  - Diploid DNA Sequence
  - Haploid DNA Sequence
  - RNA
  - Gene Expression
  - Sex Chromosomes
  - Mitochondrial DNA
  - Protein Sequence
  - Sequencing Reads
  - Phenotype
  - Single-Cell Sequencing
  - Bulk Sequencing
  - Proteomics
  - Chromatin Conformation
- Variations
  - Biallelic Marker
  - Multiallelic Marker
  - Single Nucleotide Variation
  - Amino acid variation
  - Microsatellite
  - Insertion and Deletion
  - CNV
  - Inversion and Rearrangement
  - Alternative Splicing
  - Missing Genotypes
  - Genotype or Sequencing Error
  - Ionization
  - Other
Simulation Method
- Standard Coalescent
- Exact Coalescent
- Machine Learning
- Forward-time
- Resample Existing Data
- Phylogenetic
- Gene dropping
- Neural network
- Other
Input
- Data Type
  - Allele Frequencies
  - Empirical
  - Ancestral Sequence
  - Saved simulation
  - Reference genome
  - Other
- File format
  - Arlequin
  - CREATE
  - Fstat
  - GDA
  - Genepop
  - MIGRATE
  - MS
  - SAM or BAM
  - NEXUS
  - Phylip
  - STRUCTURE
  - XML
  - Tree Sequence
  - Program Specific
  - Other
Output
- Data Type
  - Genotype or Sequence
  - Phenotypic Trait
  - Individual Relationship
  - Phylogenetic Tree
  - Demographic
  - Mutation
  - Methylation
  - Gene Expression
  - Protein Expression
  - Linkage Disequilibrium
  - Diversity Measures
  - Fitness
  - Sequencing Reads
    - Illumina
    - Roche 454
    - SOLiD
    - IonTorrent
    - PacBio
    - Nanopore
    - Other
  - Other
- File Format
  - Arlequin
  - Fasta or Fastq
  - Fstat
  - Genepop
  - Linkage
  - MIGRATE
  - MS
  - PED
  - Phylip
  - NEXUS
  - STRUCTURE
  - VCF
  - SAM or BAM
  - Tree Sequence
  - Program Specific
  - Other
- Sample Type
  - Random or Independent
  - Sibpairs, Trios and Nuclear Families
  - Extended or Complete Pedigrees
  - Case-control
  - Longitudinal
  - Other
Phenotype
- Trait Type
  - Binary or Qualitative
  - Quantitative
  - Multiple
- Determinants
  - Single Genetic Marker
  - Multiple Genetic Markers
  - Sex-linked
  - Gene-Gene Interaction
  - Environmental Factors
  - Gene-Environment Interaction
Evolutionary Features
- Demographic
  - Population Size Changes
    - Constant Size
    - Exponential Growth or Decline
    - Logistic Growth
    - Bottleneck
    - Carrying Capacity
    - User Defined
  - Gene Flow
    - Stepping Stone Models
    - Island Models
    - Continent-Island Models
    - Sex or Age-Specific Migration Rates
    - Influenced by Environmental Factors
    - Admixed Population
    - User-defined Matrix
    - Other
  - Spatiality
    - Discrete Models
    - Continuous Models
    - Landscape Factors
- Life Cycle
  - Discrete Generation Model
  - Age structured
  - Overlapping Generation
  - User-Defined transition matrices
- Mating System
  - Random Mating
  - Monogamous
  - Polygamous
  - Haplodiploid
  - Selfing
  - Age- or Stage-Specific
  - Assortative or Disassortative
  - Other
- Fecundity
  - Constant Number
  - Randomly Distributed
  - Individually Determined
  - Influenced by Environment
  - Other
- Natural Selection
  - Determinant
    - Single-locus
    - Multi-locus
    - Codon-based
    - Fitness of Offspring
    - Phenotypic Trait
    - Environmental Factors
  - Models
    - Directional Selection
    - Balancing Selection
    - Multi-locus models
    - Epistasis
    - Random Fitness Effects
    - Disruptive
    - Phenotype Threshold
    - Frequency-Dependent
    - Other
- Recombination
  - Uniform
  - Varying Recombination Rates
  - Gene Conversion Allowed
- Mutation Models
  - Two-allele Mutation Model
  - Markov DNA Evolution Models
  - k-Allele Model
  - Infinite-allele Model
  - Infinite-sites Model
  - Stepwise Mutation Model
  - Codon and Amino Acid Models
  - Indels and Others
  - Heterogeneity among Sites
  - Others
- Events Allowed
  - Population Merge and Split
  - Varying Demographic Features
  - Population Events
  - Varying Genetic Features
  - Change of Mating Systems
  - Other
- Other
  - Phenogenetic
  - Polygenic background
Interface
- Command-line
- Graphical User Interface
- Integrated Development Environment
- Script-based
- Web-based
Development
- Tested Platforms
  - Windows
  - Mac OS X
  - Linux and Unix
  - Solaris
  - Others
- Language
  - C or C++
  - Java
  - R
  - Python
  - Perl
  - Visual Basic
  - Other
- License
  - GNU Public License
  - BSD
  - Creative Commons
  - MIT
  - Other
GSR Certification
- Accessibility
- Documentation
- Application
- Support

Summary of Proposed Changes

Step 2: Review list of proposed attribute addition(s) and subtraction(s).

To Add

To Remove

Can't Find the Attribute You Are Looking For?

If you would like to propose an attribute that you cannot find in the tree above, or if you would like to add a clarification to one or more attributes for this simulator (e.g. a specific file format for attribute /Output/File Format/Other), please list them in the Additional Comment box of the Submit tab.

You may add citations by pmid, add citations by direct entry, remove citations (using the recycling bin icon), and edit citations (using the rarely seen edit icon) that were originally entered by direct entry.

Source From PMID

Summary of Proposed Changes

To Add

To Remove

Current Citations/Applications

[Pubmed ID: 21398675], Excoffier L, Foll M, fastsimcoal: a continuous-time coalescent simulator of genomic diversity under arbitrarily complex evolutionary scenarios., Bioinformatics, 05-01-2011, https://www.ncbi.nlm.nih.gov/pubmed/?term=21398675,Primary Citation

[Pubmed ID: 37066063], Maas DL, Prost S, de Leeuw CA, Bi K, Smith LL, Purwanto P, Aji LP, Tapilatu RF, Gillespie RG, Becking LE, Sponge diversification in marine lakes: Implications for phylogeography and population genomic studies on sponges., Ecol Evol, 04-13-2023, https://www.ncbi.nlm.nih.gov/pubmed/?term=37066063,, Application

[Pubmed ID: 37091563], Gilabert A, Rieux A, Robert S, Vitalis R, Zapater MF, Abadie C, Carlier J, Ravigné V, Revisiting the historical scenario of a disease dissemination using genetic data and Approximate Bayesian Computation methodology: The case of Pseudocercospora fijiensis invasion in Africa., Ecol Evol, 04-19-2023, https://www.ncbi.nlm.nih.gov/pubmed/?term=37091563,, Application