Evidence map›Paper›PMID 17660541›Full record

ArticleGenetics2007

Empirical Bayes inference of pairwise F(ST) and its distribution in the genome.

Shuichi Kitada, Toshihide Kitakado, Hirohisa Kishino

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 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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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

11 citing papers in PubMed.

  1. Article
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  8. Clinical validation of molecular markers of macrocyclic lactone resistance in Dirofilaria immitis.International journal for parasitology. Drugs and drug resistance · 2018
    Article
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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.

Shuichi KitadaFaculty of Marine Science, Tokyo University of Marine Science and Technology, Minato, Tokyo 108-8477, Japan. kitada@kaiyodai.ac.jp
Toshihide Kitakado
Hirohisa Kishino

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Populations often have very complex hierarchical structure. Therefore, it is crucial in genetic monitoring and conservation biology to have a reliable estimate of the pattern of population subdivision. F(ST)'s for pairs of sampled localities or subpopulations are crucial statistics for the exploratory analysis of population structures, such as cluster analysis and multidimensional scaling. However, the estimation of F(ST) is not precise enough to reliably estimate the population structure and the extent of heterogeneity. This article proposes an empirical Bayes procedure to estimate locus-specific pairwise F(ST)'s. The posterior mean of the pairwise F(ST) can be interpreted as a shrinkage estimator, which reduces the variance of conventional estimators largely at the expense of a small bias. The global F(ST) of a population generally varies among loci in the genome. Our maximum-likelihood estimates of global F(ST)'s can be used as sufficient statistics to estimate the distribution of F(ST) in the genome. We demonstrate the efficacy and robustness of our model by simulation and by an analysis of the microsatellite allele frequencies of the Pacific herring. The heterogeneity of the global F(ST) in the genome is discussed on the basis of the estimated distribution of the global F(ST) for the herring and examples of human single nucleotide polymorphisms (SNPs).

Indexed as

Bayes TheoremGenetics, PopulationGenetic VariationModels, GeneticAnimalsComputer SimulationFishesGene FrequencyGenomeHumansLikelihood FunctionsMicrosatellite RepeatsPolymorphism, Single NucleotideStatistics as Topic

Identifiers

PMID17660541
PMCPMC2034649

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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.