Evidence map›Paper›PMID 17507680›Full record

ArticleGenetics2007

Bayesian mapping of genomewide interacting quantitative trait loci for ordinal traits.

Nengjun Yi, Samprit Banerjee, Daniel Pomp, Brian S Yandell

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 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

20 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Bayesian mapping of genome-wide epistatic imprinted loci for quantitative traits.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2012
    Article
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  9. Article
  10. Review
  11. Article
  12. Article
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  17. Article
  18. Article
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  20. Review
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

4 authors.

Nengjun YiSection on Statistical Genetics, Department of Biostatistics, University of Alabama, Birmingham, Alabama 35294-0022, USA. nyi@ms.soph.uab.edu
Samprit Banerjee
Daniel Pomp
Brian S Yandell

Funding

Genetic Mapping of Networks Associated with Beta-cell D*R01DK066369 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI ATTIE, ALAN D · 2004 to 2014
$6.3M
The Genetics of Obesity and DiabetesR01DK058037 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI ATTIE, ALAN D · 2001 to 2013
$5.7M
Bayesian Methods for Mapping Complex Epistatic GenesR01GM069430 · NIGMS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI YI, NENGJUN · 2005 to 2013
$2.3M
QTL mapping age-related changes in lipid storageR01HL080812 · NHLBI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI DE LUCA, MARIA · 2004 to 2007
$1.3M
NHLBI NIH HHS HL080812NHLBI NIH HHS R01 HL080812NIDDK NIH HHS DK5803701NIDDK NIH HHS DK66369-01NIGMS NIH HHS R01 GM069430
6 · The paper itself

Abstract

Development of statistical methods and software for mapping interacting QTL has been the focus of much recent research. We previously developed a Bayesian model selection framework, based on the composite model space approach, for mapping multiple epistatic QTL affecting continuous traits. In this study we extend the composite model space approach to complex ordinal traits in experimental crosses. We jointly model main and epistatic effects of QTL and environmental factors on the basis of the ordinal probit model (also called threshold model) that assumes a latent continuous trait underlies the generation of the ordinal phenotypes through a set of unknown thresholds. A data augmentation approach is developed to jointly generate the latent data and the thresholds. The proposed ordinal probit model, combined with the composite model space framework for continuous traits, offers a convenient way for genomewide interacting QTL analysis of ordinal traits. We illustrate the proposed method by detecting new QTL and epistatic effects for an ordinal trait, dead fetuses, in a F(2) intercross of mice. Utility and flexibility of the method are also demonstrated using a simulated data set. Our method has been implemented in the freely available package R/qtlbim, which greatly facilitates the general usage of the Bayesian methodology for genomewide interacting QTL analysis for continuous, binary, and ordinal traits in experimental crosses.

Indexed as

Bayes TheoremEpistasis, GeneticGenomeQuantitative Trait LociAnimalsChromosome MappingFetal DeathMiceModels, Genetic

Identifiers

PMID17507680
PMCPMC1931535

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.