Evidence map›Paper›PMID 17277361›Full record

ArticleGenetics2007

Prospects for association mapping in classical inbred mouse strains.

Bret A Payseur, Michael Place

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 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

45 citing papers in PubMed.

  1. Review
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  10. Out of the bottleneck: the Diversity Outcross and Collaborative Cross mouse populations in behavioral genetics research.Mammalian genome : official journal of the International Mammalian Genome Society · 2014
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Genome-wide association studies in mice.Nature reviews. Genetics · 2012
    Review
  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

2 authors.

Bret A PayseurLaboratory of Genetics, University of Wisconsin, Madison, Wisconsin 53706, USA. payseur@wisc.edu
Michael Place

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The collection of classical inbred mouse strains displays heritable variation in a large number of complex traits. Many generations of historical recombination have contributed to the panel of classical strain genomes, raising the possibility that quantitative trait loci could be located with high resolution by correlating strain genotypes and phenotypes. Although this association mapping framework has been successful in several empirical applications, its expected performance remains unclear. We used computer simulations based on a publicly available, dense single-nucleotide polymorphism (SNP) map to measure the power and false-positive rate of association mapping on a genomic scale across 30 commonly used classical inbred strains. Expected power is (i) often low for phenotypic effect sizes that are realistic for complex traits, (ii) highly variable across the genome, and (iii) correlated with linkage disequilibrium, aspects of the allele frequency distribution, and haplotype characteristics, as predicted by theory. Simulations also demonstrate clear potential for spurious associations to be generated by unequal relatedness among the strains. These findings suggest that association mapping in the classical strains is best applied in combination with other procedures, such as QTL mapping.

Indexed as

AnimalsChromosome MappingComputer SimulationGenetic MarkersHaplotypesLinkage DisequilibriumMiceMice, Inbred StrainsModels, GeneticPhenotypePolymorphism, Single NucleotideQuantitative Trait LociGenetic Markers

Identifiers

PMID17277361
PMCPMC1855108

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.