Evidence map›Paper›PMID 17483424›Full record

ArticleGenetics2007

An efficient Bayesian model selection approach for interacting quantitative trait loci models with many effects.

Nengjun Yi, Daniel Shriner, Samprit Banerjee, Tapan Mehta, 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 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  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. Swift block-updating EM and pseudo-EM procedures for Bayesian shrinkage analysis of quantitative trait loci.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2012
    Article
  15. Article
  16. Article
  17. Article
  18. 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

6 authors.

Nengjun YiDepartment of Biostatistics, Section on Statistical Genetics, University of Alabama, Birmingham, Alabama 35294-0022, USA. nyi@ms.soph.uab.eduUT
Daniel Shriner
Samprit Banerjee
Tapan Mehta
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
UAB Obesity Training ProgramT32DK062710 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI James O Hill, Brooks C Wingo · 2004 to 2026
$5.5M
Bayesian Methods for Mapping Complex Epistatic GenesR01GM069430 · NIGMS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI YI, NENGJUN · 2005 to 2013
$2.3M
Regulation of Apolipoprotein B SecretionR01HL056593 · NHLBI · UNIVERSITY OF WISCONSIN-MADISON · PI ATTIE, ALAN D · 1998 to 2006
$1.6M
NHLBI NIH HHS HL56593NHLBI NIH HHS R01 HL056593NIDDK NIH HHS DK5803701NIDDK NIH HHS DK66369NIDDK NIH HHS T32 DK062710NIGMS NIH HHS R01 GM069430
6 · The paper itself

Abstract

We extend our Bayesian model selection framework for mapping epistatic QTL in experimental crosses to include environmental effects and gene-environment interactions. We propose a new, fast Markov chain Monte Carlo algorithm to explore the posterior distribution of unknowns. In addition, we take advantage of any prior knowledge about genetic architecture to increase posterior probability on more probable models. These enhancements have significant computational advantages in models with many effects. We illustrate the proposed method by detecting new epistatic and gene-sex interactions for obesity-related traits in two real data sets of mice. Our method has been implemented in the freely available package R/qtlbim (http://www.qtlbim.org) to facilitate the general usage of the Bayesian methodology for genomewide interacting QTL analysis.

Indexed as

Bayes TheoremModels, GeneticQuantitative Trait LociAlgorithmsAnimalsEpistasis, GeneticMarkov ChainsMiceMonte Carlo MethodObesity

Identifiers

PMID17483424
PMCPMC1931520

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.