Evidence map›Paper›PMID 23921642›Full record

ArticleHeredity2013

An evaluation of a novel estimator of linkage disequilibrium.

D Gianola, S Qanbari, H Simianer

Abstract readEvaluation Study
In one paragraph

Article in Heredity, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. 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

3 authors.

D Gianola1] Departments of Animal Sciences, Dairy Science, and Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA [2] Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, Ås, Norway.
S Qanbari
H Simianer

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The analysis of systems involving many loci is important in population and quantitative genetics. An important problem is the study of linkage disequilibrium (LD), a concept relevant in genome-enabled prediction of quantitative traits and in exploration of marker-phenotype associations. This article introduces a new estimator of a LD parameter (ρ(2)) that is much easier to compute than a maximum likelihood (or Bayesian) estimate of a tetra-choric correlation. We examined the conjecture that the sampling distribution of the estimator of ρ(2) could be less frequency dependent than that of the estimator of r(2), a widely used metric for assessing LD. This was done via an empirical evaluation of LD in 806 Holstein-Friesian cattle using 771 single-nucleotide polymorphism (SNP) markers and of HapMap III data on 21,991 SNPs (chromosome 3) observed in 88 unrelated individuals from Tuscany. Also, 1600 haplotypes over a region of 1 Mb simulated under the coalescent were used to estimate LD using the two measures. Subsequently, a simulation study compared the new estimator with that of r(2) using several scenarios of LD and allelic frequencies. From these studies, it is concluded that ρ(2) provides a useful metric for the study of LD as the distribution of its estimator is less frequency dependent than that of the standard estimator of r(2).

Indexed as

Bayes TheoremLikelihood FunctionsLinkage DisequilibriumAnimalsCattleComputer SimulationHapMap ProjectPolymorphism, Single Nucleotide

Identifiers

PMID23921642
PMCPMC3807269

What OpenQuestion holds

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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.