PhenotypeSimulator

PhenotypeSimulator simulates phenotypes for genetic studies by generating multi-trait, multi-locus data that incorporate genetic variant effects, covariate structures, observational noise, and population-structure influences (infinitesimal genetic effects) to enable evaluation of genetic analysis methods.


Key Features:

  • Multi-Trait and Multi-Locus Modeling: Simulates multiple correlated traits influenced by numerous genetic loci to reflect complex genetic architectures.
  • Covariate and Noise Structure: Incorporates complex covariate effects and observational noise to model non-genetic factors and measurement error.
  • Parameter Specification: Allows specification of genetic variant effects, population structure influences (infinitesimal genetic effects), and additional correlation effects.
  • Integration with Genetic Tools: Provides compatibility for interfacing simulated inputs and outputs with common genetic analysis tools.

Scientific Applications:

  • Method Development: Generates controlled simulated datasets for designing and testing new genetic analysis methods.
  • Assessment of Analysis Techniques: Enables evaluation of method performance in detecting genetic associations and predicting phenotypic outcomes under varied scenarios.
  • Educational Use: Produces example simulation scenarios for teaching concepts in genetics and statistical genomics.

Methodology:

Uses a simulation scheme that models multiple traits and loci, with user-specified parameters for genetic variant effects, population-structure influences (infinitesimal genetic effects), additional correlation effects, and explicit incorporation of covariate structures and observational noise.

Topics

Details

Tool Type:
library
Operating Systems:
Linux, Windows, Mac
Programming Languages:
R
Added:
6/3/2018
Last Updated:
11/25/2024

Operations

Publications

Meyer HV, Birney E. PhenotypeSimulator: A comprehensive framework for simulating multi-trait, multi-locus genotype to phenotype relationships. Bioinformatics. 2018;34(17):2951-2956. doi:10.1093/bioinformatics/bty197. PMID:29617944. PMCID:PMC6129313.

Documentation