Evidence map›Paper›PMID 20610408›Full record

ArticleGenetics2010

Optimal neutrality tests based on the frequency spectrum.

Luca Ferretti, Miguel Perez-Enciso, Sebastian Ramos-Onsins

Abstract read
In one paragraph

Article in Genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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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.

Luca FerrettiDepartment of Animal Science and Food, Universitat Autonoma de Barcelona, 08193 Bellaterra, Spain. luca.ferretti@uab.cat
Miguel Perez-Enciso
Sebastian Ramos-Onsins

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ascertainment of the demographic and selective history of populations has been a major research goal in genetics for decades. To that end, numerous statistical tests have been developed to detect deviations between expected and observed frequency spectra, e.g., Tajima's D, Fu and Li's F and D tests, and Fay and Wu's H. Recently, Achaz developed a general framework to generate tests that detect deviations in the frequency spectrum. In a further development, we argue that the results of these tests should be as independent on the sample size as possible and propose a scale-free form for them. Furthermore, using the same framework as that of Achaz, we develop a new family of neutrality tests based on the frequency spectrum that are optimal against a chosen alternative evolutionary scenario. These tests maximize the power to reject the standard neutral model and are scalable with the sample size. Optimal tests are derived for several alternative evolutionary scenarios, including demographic processes (population bottleneck, expansion, contraction) and selective sweeps. Within the same framework, we also derive an optimal general test given a generic evolutionary scenario as a null model. All formulas are relatively simple and can be computed very fast, making it feasible to apply them to genome-wide sequence data. A simulation study showed that, generally, the tests proposed are more consistently powerful than standard tests like Tajima's D. We further illustrate the method with real data from a QTL candidate region in pigs.

Indexed as

Genetic DriftAnimalsGenetics, PopulationGenomicsModels, GeneticSelection, GeneticSwine

Identifiers

PMID20610408
PMCPMC2940299

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.