Inference Under the Coalescent

Handbook of Statistical Genetics: Third Edition

Volumn 2, Issue , 2008, Pages 878-908

  Stephens, M ^a  

^a UNIVERSITY OF CHICAGO   (United States)

Author keywords

globin data; Composite likelihood; Conditional coalescent proposal; High dimensional integrals; Likelihood based inference; Markov chain Monte Carlo; PAC product of approximate conditionals likelihood; Population scaled recombination rate; Randomly sampled chromosomes; Scaled mutation parameter

Indexed keywords

EID: 84889373612     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9780470061619.ch26     Document Type: Chapter

References (49)

1. Bahlo, M. and Griffiths, R.C. (2000). Inference from gene trees in a subdivided population. Theoretical Population Biology 57, 79-95.
2. Beaumont, M. (1999). Detecting population expansion and decline using microsatellites. Genetics 153, 2013-2029.
3. Beaumont, M.A., Zhang, W. and Balding, D.J. (2002). Approximate Bayesian computation in population genetics. Genetics 162(4), 2025-2035.
4. Beerli, P. (2006). Comparison of Bayesian and maximum-likelihood inference of population genetic parameters. Bioinformatics 22(3), 341-345.
5. Beerli, P. and Felsenstein, J. (1999). Maximum likelihood estimation of migration rates and effective population numbers in two populations using a coalescent approach. Genetics 152(2), 763-773.
6. Brooks, S.P. and Roberts, G.O. (1998). Convergence assessment techniques for Markov chain Monte Carlo. Statistics and Computing 8, 319-335.
7. Chaudhuri, A.R. and Stephens, M. (2006). Fast and accurate estimation of the population scaled mutation parameters, θ, from microsatellite data. Genetics, in press.
8. Cooper, G., Amos, W., Hoffman, D. and Rubinsztein, D.C. (1996). Network analysis of human Y microsatellite haplotypes. Human Molecular Genetics 5, 1759-1766.
9. Cornuet, J.M. and Beaumont, M.A. (2007). A note on the accuracy of pac-likelihood inference with microsatellite data. Theoretical Population Biology 71(1), 12-19.
10. Excoffier, L. and Heckel, G. (2006). Computer programs for population genetics data analysis: a survival guide. Nature Reviews Genetics 7(10), 745-758.
11. Fearnhead, P. (2003). Consistency of estimators of the population-scaled recombination rate. Theoretical Population Biology 64(1), 67-79.
12. Fearnhead, P.N. and Donnelly, P. (2001). Estimating recombination rates from population genetic data. Genetics 159, 1299-1318.
13. Fearnhead, P.N. and Donnelly, P. (2002). Approximate likelihood methods for estimating local recombination rates. Journal of the Royal Statistical Society Series B 64, 657-680.
14. Felsenstein, J. (1981). Evolutionary trees from DNA sequences: a maximum likelihood approach. Journal of Molecular Evolution 17, 368-376.
15. Felsenstein, J., Kuhner, M.K., Yamato, J. and Beerli, P. (1999). Likelihoods on coalescents: a Monte Carlo sampling approach to inferring parameters from population samples of molecular data. In Statistics in Molecular Biology and Genetics, Volume 33 of IMS Lecture Notes-Monograph Series, F. Seillier-Moiseiwitsch, ed. Institute of Mathematical Statistics and American Mathematical Society, Hayward, CA, pp. 163-185.
16. Geyer, C. (1991). Reweighting Monte Carlo mixtures. Technical Report No. 568, School of Statistics, University of Minnesota. Available from http://stat.umn.edu/PAPERS/tr568r.html.
17. Gilks, W.R., Richardson, S. and Spiegelhalter, D.J. (1996). Introducing Markov chain Monte Carlo. In Markov Chain Monte Carlo in Practice, W.R. Gilks, S. Richardson and D.J. Spiegelhalter, eds. Chapman & Hall, London.
18. Griffiths, R.C. and Marjoram, P. (1996). Ancestral inference from samples of DNA sequences with recombination. Journal of Computational Biology 3, 479-502.
19. Griffiths, R.C. and Tavaré, S. (1994a). Ancestral inference in population genetics. Statistical Science 9, 307-319.
20. Griffiths, R.C. and Tavaré, S. (1994b). Sampling theory for neutral alleles in a varying environment. Philosophical Transactions of the Royal Society London Series B 344, 403-410.
21. Griffiths, R.C. and Tavaré, S. (1994c). Simulating probability distributions in the coalescent. Theoretical Population Biology 46, 131-159.
22. Griffiths, R.C. and Tavaré, S. (1997). Computational methods for the coalescent. In Progress in Population Genetics and Human Evolution, Chapter 10, Volume 87 of IMA Volumes in Mathematics and its Applications, P. Donnelly and S. Tavaré, eds. Springer Verlag, Berlin, pp. 165-182.
23. Griffiths, R.C. and Tavaré, S. (1999). The ages of mutations in gene trees. Annals of Applied Probability 9, 567-590.
24. Harding, R.M., Fullerton, S.M., Griffiths, R.C., Bond, J., Cox, M.J., Schneider, J.A., Moulin, D.S. and Clegg, J.B. (1997). Archaic African and Asian lineages in the genetic ancestry of modern humans. American Journal of Human Genetics 60, 772-789.
25. Hudson, R.R. (2001). Two-locus sampling distribution and their application. Genetics 159, 1805-1817.
26. Hudson, R.R. (2002). Generating samples under a Wright-Fisher neutral model of genetic variation. Bioinformatics 18, 337-338.
27. Huelsenbeck, J. (2001). Likelihood analysis of phylogenetic trees. In Application of the Likelihood Function in Phylogenetic Analysis. John Wiley & Sons.
28. Kuhner, M.K., Yamato, J. and Felsenstein, J. (1995). Estimating effective population size and mutation rate from sequence data using Metropolis-Hastings sampling. Genetics 140, 1421-1430.
29. Li, N. and Stephens, M. (2003). Modelling linkage disequilibrium, and identifying recombination hotspots using snp data. Genetics 165, 2213-2233.
30. Li, W.-H. and Fu, Y.-X. (1999). Coalescent theory and its application in population genetics. In Statistics in Genetics, M.E. Halloran and S. Geisser, eds. Springer, pp. 45-80.
31. Marjoram, P., Molitor, J., Plagnol, V. and Tavare, S. (2003). Markov chain Monte Carlo without likelihoods. Proceedings of the National Academy of Sciences of the United States of America 100(26), 15324-15328.
32. Marjoram, P. and Tavaré, S. (2006). Modern computational approaches for analysing molecular genetic variation data. Nature Reviews Genetics 7(10), 759-770.
33. McVean, G.A.T., Myers, S.R., Hunt, S., Deloukas, P., Bentley, D.R. and Donnelly, P. (2004). The fine-scale structure of recombination rate variation in the human genome. Science 304, 581-584.
34. Myers, S., Bottolo, L., Freeman, C., McVean, G. and Donnelly, P. (2005). A fine-scale map of recombination rates and hotspots across the human genome. Science 310(5746), 321-324.
35. Nielsen, R. (1997). A likelihood approach to population samples of microsatellite alleles. Genetics 146, 711-716.
36. Nielsen, R. (2000). Estimation of population parameters and recombination rates from single nucleotide polymorphisms. Genetics 154, 931-942.
37. Pritchard, J.K., Seielstad, M.T., Perez-Lezaun, A. and Feldman, M.W. (1999). Population growth of human Y chromosomes: a study of Y chromosome microsatellites. Molecular Biology and Evolution 16(12), 1791-1798.
38. Ripley, B.D. (1987). Stochastic Simulation. John Wiley & Sons, New York.
39. Schaffner, S.F., Foo, C., Gabriel, S., Reich, D., Daly, M.J. and Altshuler, D. (2005). Calibrating a coalescent simulation of human genome sequence variation. Genome Research 15(11), 1576-1583.
40. Sisson, S.A., Fan, Y. and Tanaka, M.M. (2007). Sequential Monte Carlo without likelihoods. Proceedings of the National Academy of Sciences 104, 1760-1765.
41. Smith, N. and Fearnhead, P. (2005). A comparison of three estimators of the population-scaled recombination rate: accuracy and robustness. Genetics 171(4), 2051-2062.
42. Spencer, C.C. and Coop, G. Selsim: a program to simulate population genetic data with natural selection and recombination. Bioinformatics 20(18), 3673-3675.
43. Stephens, M. (1999). Problems with computational methods in population genetics, 273-276. Available from http://www.stats.ox.ac.uk/~stephens.
44. Stephens, M. and Donnelly, P. (2000). Inference in molecular population genetics. Journal of the Royal Statistical Society Series B 62, 605-655.
45. Stephens, M. and Scheet, P. (2005). Accounting for decay of linkage disequilibrium in haplotype inference and missing data imputation. American Journal of Human Genetics 76, 449-462.
46. Tavaré, S., Balding, D.J., Griffiths, R.C. and Donnelly, P. (1997). Inferring coalescence times from DNA sequence data. Genetics 145, 505-518.
47. Tremblay, M. and Vézina, H. (2000). New estimates of intergenerational time intervals for the calculation of age and origins of mutations. American Journal of Human Genetics 66, 651-658.
48. Weiss, K. (1973). Demographic models for anthropology. American Antiquity 38, 1-186.
49. Wilson, I.J. and Balding, D.J. (1998). Genealogical inference from microsatellite data. Genetics 150, 499-510.