Skip to main content
PMC home page
Genetics logoLink to Genetics
. 2004 Jun;167(2):977–988. doi: 10.1534/genetics.103.026146

Comparative evaluation of a new effective population size estimator based on approximate bayesian computation.

David A Tallmon 1, Gordon Luikart 1, Mark A Beaumont 1
PMCID: PMC1470910  PMID: 15238546

Abstract

We describe and evaluate a new estimator of the effective population size (N(e)), a critical parameter in evolutionary and conservation biology. This new "SummStat" N(e) estimator is based upon the use of summary statistics in an approximate Bayesian computation framework to infer N(e). Simulations of a Wright-Fisher population with known N(e) show that the SummStat estimator is useful across a realistic range of individuals and loci sampled, generations between samples, and N(e) values. We also address the paucity of information about the relative performance of N(e) estimators by comparing the SummStat estimator to two recently developed likelihood-based estimators and a traditional moment-based estimator. The SummStat estimator is the least biased of the four estimators compared. In 32 of 36 parameter combinations investigated using initial allele frequencies drawn from a Dirichlet distribution, it has the lowest bias. The relative mean square error (RMSE) of the SummStat estimator was generally intermediate to the others. All of the estimators had RMSE > 1 when small samples (n = 20, five loci) were collected a generation apart. In contrast, when samples were separated by three or more generations and N(e) < or = 50, the SummStat and likelihood-based estimators all had greatly reduced RMSE. Under the conditions simulated, SummStat confidence intervals were more conservative than the likelihood-based estimators and more likely to include true N(e). The greatest strength of the SummStat estimator is its flexible structure. This flexibility allows it to incorporate any potentially informative summary statistic from population genetic data.

Full Text

The Full Text of this article is available as a PDF (155.3 KB).

Selected References

These references are in PubMed. This may not be the complete list of references from this article.

  1. Beaumont Mark A., Zhang Wenyang, Balding David J. Approximate Bayesian computation in population genetics. Genetics. 2002 Dec;162(4):2025–2035. doi: 10.1093/genetics/162.4.2025. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Berthier Pierre, Beaumont Mark A., Cornuet Jean-Marie, Luikart Gordon. Likelihood-based estimation of the effective population size using temporal changes in allele frequencies: a genealogical approach. Genetics. 2002 Feb;160(2):741–751. doi: 10.1093/genetics/160.2.741. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Fu Y. X., Li W. H. Estimating the age of the common ancestor of a sample of DNA sequences. Mol Biol Evol. 1997 Feb;14(2):195–199. doi: 10.1093/oxfordjournals.molbev.a025753. [DOI] [PubMed] [Google Scholar]
  4. Nei M., Tajima F. Genetic drift and estimation of effective population size. Genetics. 1981 Jul;98(3):625–640. doi: 10.1093/genetics/98.3.625. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Pritchard J. K., Seielstad M. T., Perez-Lezaun A., Feldman M. W. Population growth of human Y chromosomes: a study of Y chromosome microsatellites. Mol Biol Evol. 1999 Dec;16(12):1791–1798. doi: 10.1093/oxfordjournals.molbev.a026091. [DOI] [PubMed] [Google Scholar]
  6. Shoemaker J. S., Painter I. S., Weir B. S. Bayesian statistics in genetics: a guide for the uninitiated. Trends Genet. 1999 Sep;15(9):354–358. doi: 10.1016/s0168-9525(99)01751-5. [DOI] [PubMed] [Google Scholar]
  7. Spencer C. C., Neigel J. E., Leberg P. L. Experimental evaluation of the usefulness of microsatellite DNA for detecting demographic bottlenecks. Mol Ecol. 2000 Oct;9(10):1517–1528. doi: 10.1046/j.1365-294x.2000.01031.x. [DOI] [PubMed] [Google Scholar]
  8. Storz Jay F., Ramakrishnan Uma, Alberts Susan C. Genetic effective size of a wild primate population: influence of current and historical demography. Evolution. 2002 Apr;56(4):817–829. doi: 10.1111/j.0014-3820.2002.tb01392.x. [DOI] [PubMed] [Google Scholar]
  9. Tavaré S., Balding D. J., Griffiths R. C., Donnelly P. Inferring coalescence times from DNA sequence data. Genetics. 1997 Feb;145(2):505–518. doi: 10.1093/genetics/145.2.505. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Tishkoff S. A., Varkonyi R., Cahinhinan N., Abbes S., Argyropoulos G., Destro-Bisol G., Drousiotou A., Dangerfield B., Lefranc G., Loiselet J. Haplotype diversity and linkage disequilibrium at human G6PD: recent origin of alleles that confer malarial resistance. Science. 2001 Jun 21;293(5529):455–462. doi: 10.1126/science.1061573. [DOI] [PubMed] [Google Scholar]
  11. Vitalis R., Couvet D. Estimation of effective population size and migration rate from one- and two-locus identity measures. Genetics. 2001 Feb;157(2):911–925. doi: 10.1093/genetics/157.2.911. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Wang J. A pseudo-likelihood method for estimating effective population size from temporally spaced samples. Genet Res. 2001 Dec;78(3):243–257. doi: 10.1017/s0016672301005286. [DOI] [PubMed] [Google Scholar]
  13. Wang Jinliang, Whitlock Michael C. Estimating effective population size and migration rates from genetic samples over space and time. Genetics. 2003 Jan;163(1):429–446. doi: 10.1093/genetics/163.1.429. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Waples R. S. A generalized approach for estimating effective population size from temporal changes in allele frequency. Genetics. 1989 Feb;121(2):379–391. doi: 10.1093/genetics/121.2.379. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Weiss G., von Haeseler A. Inference of population history using a likelihood approach. Genetics. 1998 Jul;149(3):1539–1546. doi: 10.1093/genetics/149.3.1539. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Williamson E. G., Slatkin M. Using maximum likelihood to estimate population size from temporal changes in allele frequencies. Genetics. 1999 Jun;152(2):755–761. doi: 10.1093/genetics/152.2.755. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Genetics are provided here courtesy of Oxford University Press

RESOURCES