Evidence map›Paper›PMID 12702692›Full record

ArticleGenetics2003

Fine mapping of complex trait genes combining pedigree and linkage disequilibrium information: a Bayesian unified framework.

Miguel Pérez-Enciso

Abstract read
In one paragraph

Article in Genetics, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Clusthaplo: a plug-in for MCQTL to enhance QTL detection using ancestral alleles in multi-cross design.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2014
    Article
  5. Article
  6. Article
  7. Article
  8. A fast expectation-maximum algorithm for fine-scale QTL mapping.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2012
    Article
  9. Article
  10. Review
  11. Article
  12. A gene frequency model for QTL mapping using Bayesian inference.Genetics, selection, evolution : GSE · 2010
    Article
  13. Article
  14. Article
  15. Linear models for joint association and linkage QTL mapping.Genetics, selection, evolution : GSE · 2009
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

1 author.

Miguel Pérez-EncisoInstitut National de la Recherche Agronomique, Station d'Amélioration Génétique des Animaux, 31326 Castanet-Tolosan, France. mperez@toulouse.inra.fr

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a Bayesian method that combines linkage and linkage disequilibrium (LDL) information for quantitative trait locus (QTL) mapping. This method uses jointly all marker information (haplotypes) and all available pedigree information; i.e., it is not restricted to any specific experimental design and it is not required that phases are known. Infinitesimal genetic effects or environmental noise ("fixed") effects can equally be fitted. A diallelic QTL is assumed and both additive and dominant effects can be estimated. We have implemented a combined Gibbs/Metropolis-Hastings sampling to obtain the marginal posterior distributions of the parameters of interest. We have also implemented a Bayesian variant of usual disequilibrium measures like D' and r(2) between QTL and markers. We illustrate the method with simulated data in "simple" (two-generation full-sib families) and "complex" (four-generation) pedigrees. We compared the estimates with and without using linkage disequilibrium information. In general, using LDL resulted in estimates of QTL position that were much better than linkage-only estimates when there was complete disequilibrium between the mutant QTL allele and the marker. This advantage, however, decreased when the association was only partial. In all cases, additive and dominant effects were estimated accurately either with or without disequilibrium information.

Indexed as

Bayes TheoremGenetic LinkageLinkage DisequilibriumQuantitative Trait LociChromosome MappingComputer SimulationData Interpretation, Statistical

Identifiers

PMID12702692
PMCPMC1462504

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.