phenosim

phenosim simulates phenotypes for genotypes produced by coalescent simulations to model additive and epistatic genetic effects, generate qualitative and quantitative traits, and assess statistical power in genome-wide association studies.


Key Features:

  • Integration with Coalescent Simulations: Reads outputs from coalescent simulators and uses those genotypes to simulate qualitative and quantitative phenotypes according to user-defined parameters and demographic models.
  • Phenotypic Variation Modeling: Partitions phenotypic variation into additive effects and epistatic interactions among causal genetic variants.
  • Output Compatibility: Produces output formats compatible with GWAS tools for downstream association analyses.
  • Assessment of Statistical Power: Simulates phenotypes alongside genotypes to evaluate how demography, genetic architecture, and selection influence the statistical power of association methods.

Scientific Applications:

  • Genome-wide association study simulation: Generates genotype–phenotype datasets for GWAS, including use cases in Arabidopsis thaliana.
  • Power and method evaluation: Assesses the impact of demography, genetic architecture, and selection on detection of causal variants and statistical power of association methods.
  • Complex trait and population genetics research: Models additive and epistatic interactions and multiple trait types to investigate genetic architectures and trait evolution.

Methodology:

Consumes genotype data produced by coalescent simulations and adds phenotypes (qualitative and quantitative) according to specified parameters, partitioning effects into additive components and epistatic interactions.

Topics

Details

Tool Type:
desktop application
Operating Systems:
Linux, Windows, Mac
Programming Languages:
Python
Added:
8/3/2017
Last Updated:
11/25/2024

Operations

Publications

Günther T, Gawenda I, Schmid KJ. phenosim - A software to simulate phenotypes for testing in genome-wide association studies. BMC Bioinformatics. 2011;12(1). doi:10.1186/1471-2105-12-265. PMID:21714868. PMCID:PMC3150295.

Documentation

Links