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Model-free linkage analysis using likelihoods

D Curtis1, P C Sham

  • 1Department of Psychological Medicine, Institute of Psychiatry, London, United Kingdom.

American Journal of Human Genetics
|September 1, 1995
PubMed
Summary
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This study introduces a novel linkage detection method that avoids biased parameter estimates by focusing on detecting genetic effects rather than precise locus mapping. The new approach offers a powerful and reliable tool for genetic linkage analysis in various family structures.

Area of Science:

  • Genetics
  • Statistical genetics
  • Bioinformatics

Background:

  • Transmission model parameter misspecification can lead to inaccurate lod scores in genetic linkage analysis.
  • Estimating linkage and transmission parameters simultaneously can result in biased estimates and reduced power.

Purpose of the Study:

  • To develop a robust statistical test for detecting genetic effects at a specific locus, independent of precise map position estimation.
  • To overcome limitations of traditional linkage analysis methods, particularly in multipoint analyses and with small recombination fractions.

Main Methods:

  • A novel linkage test was devised, focusing on detecting a genetic effect at a locus rather than estimating its exact position.
  • Likelihoods were maximized over a limited set of transmission models, constrained by population prevalence.

Related Experiment Videos

  • The test involves maximizing the likelihood under linkage over admixture (proportion of linked families).

    • Main Results:

    • The proposed method demonstrates robust performance under the null hypothesis in simulations across diverse transmission models and family types (sib pairs, pedigrees).
    • The test provides high power for detecting linkage when a genetic effect is present.
    • The method is suitable for both affected sib pair and pedigree analyses, including multipoint data.

    Conclusions:

    • This new linkage detection method effectively avoids biases associated with transmission model misspecification.
    • It offers a powerful and versatile alternative for genetic linkage analysis, requiring only an approximate population prevalence estimate.
    • The approach is applicable to various family structures and suitable for multipoint analyses without diminishing lod scores near markers.