Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 422

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Methods to Detect Selection in Populations with Applications to the Human

Kreitman, Martin·2000·Annual Review of Genomics and Human Genetics

Abstract

The development of statistical tests of natural selection at the DNA level in population samples has been ongoing for the past 13 years. The current state of the field is reviewed, and the available tests of selection are described. All tests use predictions from the theory of neutrally evolving sites as a null hypothesis. Departures from equilibrium-neutral expectations can indicate the presence of natural selection acting either at one or more of the sites under investigation or at a sufficiently tightly linked site. Complications can arise in the interpretation of departures from neutrality if populations are not at equilibrium for mutation and genetic drift or if populations are subdivided, both of which are likely scenarios for humans. Attempts to understand the nonequilibrium configuration of silent polymorphism in human mitochondrial DNA illustrate the difficulty of distinguishing between selection and alternative demographic hypotheses. The range of plausible alternatives to selection will become better defined, however, as additional population genetic data sets become available, allowing better null models to be constructed.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1146/annurev.genom.1.1.539

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Cited by

Metadata

Authors
Kreitman, M.
Venue
Annual Review of Genomics and Human Genetics
Published
2000-09
Volume
1
Issue
1
Pages
539-559
ISSN
  • 1527-8204 (ISSN-L)
  • 1545-293X
OpenAlex
W2096866954
Cited by
422
References
2
FWCI
1.31
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 ›

Are you an author, or do you see a problem with this page? Request a review

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.