Evidence map›Paper›PMID 19477986›Full record

ArticleBioinformatics (Oxford, England)2009

Multi-locus match probability in a finite population: a fundamental difference between the Moran and Wright-Fisher models.

Anand Bhaskar, Yun S Song

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Forensic genetics through the lens of Lewontin: population structure, ancestry and race.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
    Review
  2. Pseudoreplication in genomic-scale data sets.Molecular ecology resources · 2022
    Article
  3. Article
  4. Review
  5. Distortion of genealogical properties when the sample is very large.Proceedings of the National Academy of Sciences of the United States of America · 2014
    Article
  6. Match probabilities in a finite, subdivided population.Theoretical population biology · 2011
    Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Anand BhaskarComputer Science Division and Department of Statistics, University of California, Berkeley, CA, USA.
Yun S Song

Funding

Novel Methods for Characterizing Recombination and SelectionR00GM080099 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI SONG, YUN S · 2008 to 2010
$744k
NIGMS NIH HHS R00 GM080099NIGMS NIH HHS R00-GM080099
6 · The paper itself

Abstract

motivationA fundamental problem in population genetics, which being also of importance to forensic science, is to compute the match probability (MP) that two individuals randomly chosen from a population have identical alleles at a collection of loci. At present, 11-13 unlinked autosomal microsatellite loci are typed for forensic use. In a finite population, the genealogical relationships of individuals can create statistical non-independence of alleles at unlinked loci. However, the so-called product rule, which is used in courts in the USA, computes the MP for multiple unlinked loci by assuming statistical independence, multiplying the one-locus MPs at those loci. Analytically testing the accuracy of the product rule for more than five loci has hitherto remained an open problem.

resultsIn this article, we adopt a flexible graphical framework to compute multi-locus MPs analytically. We consider two standard models of random mating, namely the Wright-Fisher (WF) and Moran models. We succeed in computing haplotypic MPs for up to 10 loci in the WF model, and up to 13 loci in the Moran model. For a finite population and a large number of loci, we show that the MPs predicted by the product rule are highly sensitive to mutation rates in the range of interest, while the true MPs computed using our graphical framework are not. Furthermore, we show that the WF and Moran models may produce drastically different MPs for a finite population, and that this difference grows with the number of loci and mutation rates. Although the two models converge to the same coalescent or diffusion limit, in which the population size approaches infinity, we demonstrate that, when multiple loci are considered, the rate of convergence in the Moran model is significantly slower than that in the WF model. AVAILABILITY: A C++ implementation of the algorithms discussed in this article is available at http://www.cs.berkeley.edu/ approximately yss/software.html.

Indexed as

Models, GeneticComputational BiologyGenetics, PopulationPopulation DensityPopulation DynamicsProbability

Identifiers

PMID19477986
PMCPMC2687981

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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.