Evidence map›Paper›PMID 17435239›Full record

ArticleGenetics2007

Bayesian shrinkage analysis of quantitative trait Loci for dynamic traits.

Runqing Yang, Shizhong Xu

Abstract read
In one paragraph

Article in Genetics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Mapping complex traits as a dynamic system.Physics of life reviews · 2015
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Bayesian functional mapping of dynamic quantitative traits.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2011
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Runqing YangSchool of Agriculture and Biology, Shanghai Jiaotong University, Shanghai 201101, People's Republic of China.
Shizhong Xu

Funding

RANDOM MODEL METHODOLOGY FOR GENE MAPPINGR01GM055321 · NIGMS · UNIVERSITY OF CALIFORNIA RIVERSIDE · PI XU, SHIZHONG · 1997 to 2005
$663k
NIGMS NIH HHS R01 GM055321NIGMS NIH HHS R01-GM55321
6 · The paper itself

Abstract

Many quantitative traits are measured repeatedly during the life of an organism. Such traits are called dynamic traits. The pattern of the changes of a dynamic trait is called the growth trajectory. Studying the growth trajectory may enhance our understanding of the genetic architecture of the growth trajectory. Recently, we developed an interval-mapping procedure to map QTL for dynamic traits under the maximum-likelihood framework. We fit the growth trajectory by Legendre polynomials. The method intended to map one QTL at a time and the entire QTL analysis involved scanning the entire genome by fitting multiple single-QTL models. In this study, we propose a Bayesian shrinkage analysis for estimating and mapping multiple QTL in a single model. The method is a combination between the shrinkage mapping for individual quantitative traits and the Legendre polynomial analysis for dynamic traits. The multiple-QTL model is implemented in two ways: (1) a fixed-interval approach where a QTL is placed in each marker interval and (2) a moving-interval approach where the position of a QTL can be searched in a range that covers many marker intervals. Simulation study shows that the Bayesian shrinkage method generates much better signals for QTL than the interval-mapping approach. We propose several alternative methods to present the results of the Bayesian shrinkage analysis. In particular, we found that the Wald test-statistic profile can serve as a mechanism to test the significance of a putative QTL.

Indexed as

Bayes TheoremModels, GeneticQuantitative Trait LociCrosses, GeneticKineticsMathematics

Identifiers

PMID17435239
PMCPMC1894582

What OpenQuestion holds

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Registered trials

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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.