ArticleG3 (Bethesda, Md.)2013
Detecting selection using time-series data of allele frequencies with multiple independent reference Loci.
Article in G3 (Bethesda, Md.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.
What it found
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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.
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.
Who cites it
5 citing papers in PubMed.
- Article
- Measuring viability selection from prospective cohort mortality studies: A case study in maritime pine.Evolutionary applications · 2019Article
- The Effects of Population Size Histories on Estimates of Selection Coefficients from Time-Series Genetic Data.Molecular biology and evolution · 2016Article
- Efficiently tracking selection in a multiparental population: the case of earliness in wheat.Genetics · 2015Article
- Population genetics inference for longitudinally-sampled mutants under strong selection.Genetics · 2014Article
Corrections and comments
- Erratum issued
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recently, in 2013 Feder et al. proposed the frequency increment test (FIT), which evaluates natural selection at a single diallelic locus by the use of time-series data of allele frequencies. This test is unbiased under conditions of constant population size and no sampling noise. Here, we expand upon the FIT by introducing a test that explicitly allows for changes in population size by using information from independent reference loci. Various demographic models suggest that our proposed test is unbiased irrespective of fluctuations in population size when sampling noise can be ignored and that it has greater power to detect selection than the FIT if sufficient reference loci are used.
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Registered trials
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