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A Composite-Conditional-Likelihood Approach for Gene Mapping Based on Linkage Disequilibrium in Windows of Marker Loci

Author

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  • Larribe Fabrice

    (Université du Québec à Montréal)

  • Lessard Sabin

    (Université de Montréal)

Abstract

A composite-conditional-likelihood (CCL) approach is proposed to map the position of a trait-influencing mutation (TIM) using the ancestral recombination graph (ARG) and importance sampling to reconstruct the genealogy of DNA sequences with respect to windows of marker loci and predict the linkage disequilibrium pattern observed in a sample of cases and controls. The method is designed to fine-map the location of a disease mutation, not as an association study. The CCL function proposed for the position of the TIM is a weighted product of conditional likelihood functions for windows of a given number of marker loci that encompass the TIM locus, given the sample configuration at the marker loci in those windows. A rare recessive allele is assumed for the TIM and single nucleotide polymorphisms (SNPs) are considered as markers. The method is applied to a range of simulated data sets. Not only do the CCL profiles converge more rapidly with smaller window sizes as the number of simulated histories of the sampled sequences increases, but the maximum-likelihood estimates for the position of the TIM remain as satisfactory, while requiring significantly less computing time. The simulations also suggest that non-random samples, more precisely, a non-proportional number of controls versus the number of cases, has little effect on the estimation procedure as well as sample size and marker density beyond some threshold values. Moreover, when compared with some other recent methods under the same assumptions, the CCL approach proves to be competitive.

Suggested Citation

  • Larribe Fabrice & Lessard Sabin, 2008. "A Composite-Conditional-Likelihood Approach for Gene Mapping Based on Linkage Disequilibrium in Windows of Marker Loci," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 7(1), pages 1-33, August.
    • Handle: RePEc:bpj:sagmbi:v:7:y:2008:i:1:n:27
    DOI: 10.2202/1544-6115.1298
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    References listed on IDEAS

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    1. Cristiano Varin, 2008. "On composite marginal likelihoods," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(1), pages 1-28, February.
    2. Cristiano Varin & Paolo Vidoni, 2005. "A note on composite likelihood inference and model selection," Biometrika, Biometrika Trust, vol. 92(3), pages 519-528, September.
    3. Paul Fearnhead & Peter Donnelly, 2002. "Approximate likelihood methods for estimating local recombination rates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 657-680, October.
    4. Matthew Stephens & Peter Donnelly, 2000. "Inference in molecular population genetics," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 605-635.
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    1. Griffiths, Robert C. & Jenkins, Paul A. & Lessard, Sabin, 2016. "A coalescent dual process for a Wright–Fisher diffusion with recombination and its application to haplotype partitioning," Theoretical Population Biology, Elsevier, vol. 112(C), pages 126-138.
    2. Kenne Pagui, E.C. & Salvan, A. & Sartori, N., 2015. "On full efficiency of the maximum composite likelihood estimator," Statistics & Probability Letters, Elsevier, vol. 97(C), pages 120-124.
    3. Hössjer Ola & Hartman Linda & Humphreys Keith, 2009. "Ancestral Recombination Graphs under Non-Random Ascertainment, with Applications to Gene Mapping," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-46, September.

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