Evidence map›Paper›PMID 21115971›Full record

ArticleGenetics2011

A model selection approach for expression quantitative trait loci (eQTL) mapping.

Ping Wang, John A Dawson, Mark P Keller, Brian S Yandell, Nancy A Thornberry, Bei B Zhang, I-Ming Wang, Eric E Schadt, Alan D Attie, C Kendziorski

Abstract read
In one paragraph

Article in Genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. The genetic basis of obesity-associated type 2 diabetes (diabesity) in polygenic mouse models.Mammalian genome : official journal of the International Mammalian Genome Society · 2014
    Review
  8. Finding alternative expression quantitative trait loci by exploring sparse model space.Journal of computational biology : a journal of computational molecular cell biology · 2014
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. 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

10 authors.

Ping WangDepartment of Statistics, University of Wisconsin, Madison, Wisconsin 53726, USA.
John A Dawson
Mark P Keller
Brian S Yandell
Nancy A Thornberry
Bei B Zhang
I-Ming Wang
Eric E Schadt
Alan D Attie
C Kendziorski

Funding

PHS HHS 58037PHS HHS 66369PHS HHS 74904PHS HHS 76274
6 · The paper itself

Abstract

Identifying the genetic basis of complex traits remains an important and challenging problem with the potential to affect a broad range of biological endeavors. A number of statistical methods are available for mapping quantitative trait loci (QTL), but their application to high-throughput phenotypes has been limited as most require user input and interaction. Recently, methods have been developed specifically for expression QTL (eQTL) mapping, but they too are limited in that they do not allow for interactions and QTL of moderate effect. We here propose an automated model-selection-based approach that identifies multiple eQTL in experimental populations, allowing for eQTL of moderate effect and interactions. Output can be used to identify groups of transcripts that are likely coregulated, as demonstrated in a study of diabetes in mouse.

Indexed as

Chromosome MappingModels, GeneticAnimalsComputational BiologyGene Expression ProfilingGene Expression RegulationMiceMice, Inbred C57BLPhenotypeQuantitative Trait Loci

Identifiers

PMID21115971
PMCPMC3030500

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.