Evidence map›Paper›PMID 11404347›Full record

ArticleGenetics2001

The use of intraallelic variability for testing neutrality and estimating population growth rate.

M Slatkin, G Bertorelle

Abstract read
In one paragraph

Article in Genetics, 2001. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
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  11. Article
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  15. Article
  16. Article
  17. Article
  18. The genetic legacy of the Mongols.American journal of human genetics · 2003
    Article
  19. Article
  20. Article
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

2 authors.

M SlatkinDepartment of Integrative Biology, University of California, Berkeley, CA 94720-3140, USA. slatkin@socrates.berkeley.edu
G Bertorelle

Funding

MODELS OF COMPLEX GENETIC SYSTEMSR01GM040282 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI SLATKIN, MONTGOMERY WILSON · 1988 to 2017
$4.4M
NIGMS NIH HHS GM40282
6 · The paper itself

Abstract

To better understand the forces affecting individual alleles, we introduce a method for finding the joint distribution of the frequency of a neutral allele and the extent of variability at closely linked marker loci (the intraallelic variability). We model three types of intraallelic variability: (a) the number of nonrecombinants at a linked biallelic marker locus, (b) the length of a conserved haplotype, and (c) the number of mutations at a linked marker locus. If the population growth rate is known, the joint distribution provides the basis for a test of neutrality by testing whether the observed level of intraallelic variability is consistent with the observed allele frequency. If the population growth rate is unknown but neutrality can be assumed, the joint distribution provides the likelihood of the growth rate and leads to a maximum-likelihood estimate. We apply the method to data from published data sets for four loci in humans. We conclude that the Delta32 allele at CCR5 and a disease-associated allele at MLH1 arose recently and have been subject to strong selection. Alleles at PAH appear to be neutral and we estimate the recent growth rate of the European population to be approximately 0.027 per generation with a support interval of (0.017-0.037). Four of the relatively common alleles at CFTR also appear to be neutral but DeltaF508 appears to be significantly advantageous to heterozygous carriers.

Indexed as

Genetic VariationAllelesCystic Fibrosis Transmembrane Conductance RegulatorGene FrequencyHeterozygoteHumansLikelihood FunctionsModels, GeneticModels, StatisticalReceptors, CCR5Recombination, GeneticCFTR protein, humanCystic Fibrosis Transmembrane Conductance RegulatorReceptors, CCR5

Identifiers

PMID11404347
PMCPMC1461666

What OpenQuestion holds

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Registered trials

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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.