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LINKERS: a simulation programming system for generating populations with genetic structure.

J J Yang1, E Ackerman, S S Rich

  • 1Division of Health Computer Sciences, University of Minnesota, Minneapolis 55455.

Computers in Biology and Medicine
|January 1, 1990
PubMed
Summary
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The LINKERS simulation system efficiently generates nuclear family genetic data for complex trait studies. This tool aids in understanding genetic ascertainment and analyzing genetic models with multiple alleles and varying gene frequencies.

Area of Science:

  • Computational Biology
  • Genetics
  • Bioinformatics

Background:

  • Genetic ascertainment studies require large, realistic datasets.
  • Existing simulation tools may lack user-friendliness or efficiency.
  • Monte Carlo methods are valuable for simulating complex biological systems.

Purpose of the Study:

  • To introduce LINKERS, a Monte Carlo simulation system for generating nuclear family genetic data.
  • To demonstrate the system's efficiency and user-friendly design.
  • To facilitate studies on genetic ascertainment and model analysis.

Main Methods:

  • Utilized software engineering techniques for a user-friendly environment.
  • Developed 39 code modules maintained and optimized with VAXset.

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  • Implemented a VAX/VMS workstation environment for rapid data generation.

    • Main Results:

    • LINKERS generates 10,000 nuclear families in approximately 1 minute.
    • The system supports one and two loci genetic models.
    • Analysis of simulated data revealed the impact of multiple alleles, gene frequency, and disease prevalence specification.

    Conclusions:

    • LINKERS provides an efficient and user-friendly platform for generating nuclear family genetic data.
    • The simulation system is valuable for genetic ascertainment research.
    • Accurate genetic model specification is crucial for reliable analysis.