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Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.
Abstract
The relationship between the two estimates of genetic variation at the DNA level, namely the number of segregating sites and the average number of nucleotide differences estimated from pairwise comparison, is investigated. It is found that the correlation between these two estimates is large when the sample size is small, and decreases slowly as the sample size increases. Using the relationship obtained, a statistical method for testing the neutral mutation hypothesis is developed. This method needs only the data of DNA polymorphism, namely the genetic variation within population at the DNA level. A simple method of computer simulation, that was used in order to obtain the distribution of a new statistic developed, is also presented. Applying this statistical method to the five regions of DNA sequences in Drosophila melanogaster, it is found that large insertion/deletion (greater than 100 bp) is deleterious. It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.
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Palstra, F. P., Heyer, E., & Austerlitz, F. (2015) · Molecular Biology and Evolution · doi:10.1093/molbev/msv030 · Cited by 36
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PopHuman: the human population genomics browser
Casillas, S., Mulet, R., Villegas-Mirón, P., Hervas, S., Sanz, E., Velasco, D., Bertranpetit, J., Laayouni, H., & Barbadilla, A. (2018) · Nucleic Acids Research · doi:10.1093/nar/gkx943 · Cited by 29
Metadata
- Authors
- Tajima, F.
- Venue
- Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 1989-11-01
- Volume
- 123
- Issue
- 3
- Pages
- 585-595
- ISSN
- 0016-6731 (ISSN-L)
- 1943-2631
- OpenAlex
- W2140784970
- Cited by
- 13,941
- References
- 2
- FWCI
- 3.56
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.