General quantitative genetic methods for comparative biology: Phylogenies, taxonomies and multi-trait models for continuous and categorical characters

Journal of Evolutionary Biology

Volumn 23, Issue 3, 2010, Pages 494-508

  Hadfield, J D ^a   Nakagawa, S ^b  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

^b UNIVERSITY OF OTAGO   (New Zealand)

Author keywords

Comparative method; Meta analysis; Pedigree; Phylogeny; Quantitative genetics

Indexed keywords

ALGORITHM; COMPARATIVE STUDY; EVOLUTIONARY BIOLOGY; MARKOV CHAIN; META-ANALYSIS; MONTE CARLO ANALYSIS; PHYLOGENY; TAXONOMY;

ANIMAL; ARTICLE; BIOLOGICAL MODEL; BIOLOGY; GENETIC PROCEDURES; META ANALYSIS; METHODOLOGY; MONTE CARLO METHOD; PHYLOGENY; PROBABILITY;

ANIMALS; COMPUTATIONAL BIOLOGY; GENETIC TECHNIQUES; MARKOV CHAINS; META-ANALYSIS AS TOPIC; MODELS, GENETIC; MONTE CARLO METHOD; PHYLOGENY;

EID: 77749279661     PISSN: 1010061X     EISSN: 14209101     Source Type: Journal    
DOI: 10.1111/j.1420-9101.2009.01915.x     Document Type: Article

References (85)

1. Adams DC. Phylogenetic meta-analysis. Evolution 2008, 62:567-572.
2. Becker BJ. Fail safe n or file-drawer number. Publication Bias in Meta-analysis: Prevention, Assessment and Adjustments 2005, 111-125. Rothstein HSutton AJBorenstein M. In, eds.), pp, John Wiley, Chichester
3. Bergmann C. Über die verhältnisse der wärmeökonomie der thiere zu ihrer grosse. Göttinger Studien 1847, 1:595-708.
4. Bininda-Emonds ORP, Cardillo M, Jones KE, MacPhee RDE, Beck RMD, Grenyer R, Price SA, Vos RA, Gittleman JL, Purvis A. The delayed rise of present-day mammals. Nature 2007, 446:507-512.
5. Bunch DS. Estimability in the multinomial probit model. Transport. Res. B-Meth. 1991, 25:1-12.
6. Clutton-Brock TH, Harvey PH. Primate ecology and social-organization. J. Zool. 1977, 183:1-39.
7. Congdon P. Applied Bayesian Modelling. Wiley Series in Probability and Statistics 2003, Wiley, Chichester
8. Congdon P. Bayesian Models for Categorical Data. Wiley Series in Probability and Statistics 2005, Wiley-Blackwell, Chichester
9. Daganzo C. Multinomial Probit: The Theory and Its Application to Demand Forecasting 1979, Academic Press, New York
10. Davis TA. Direct Methods for Sparse Linear Systems 2006, Fundamentals of Algorithms, SIAM, Philadelphia, PA
11. Dempster AP, Laird NM, Rubin DB. Maximum likelihood from incomplete data via EM algorithm. J. R. Stat. Soc. Ser. B-Stat. Methodol. 1977, 39:1-38.
12. Diniz-Filho JAF, De Sant'ana CER, Bini LM. An eigenvector method for estimating phylogenetic inertia. Evolution 1998, 52:1247-1262.
13. Duval S. The trim and fill method. Publication Bias in Meta-analysis: Prevention, Assessment and Adjustments 2005, 127-144. Rothstein HSutton AJBorenstein M. In, eds.), pp, John Wiley, Chichester
14. Duval S, Tweedie R. A nonparametric ''trim and fill'' method of accounting for publication bias in meta-analysis. J. Am. Stat. Assoc. 2000a, 95:89-98.
15. Duval S, Tweedie R. Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics 2000b, 56:455-463.
16. Falconer D. Introduction to Quantitative Genetics 1983, Longman Group, Harlow, UK
17. Felsenstein J. Phylogenies and the comparative method. Am. Nat. 1985, 125:1-15.
18. Felsenstein J. Using the quantitative genetic threshold model for inferences between and within species. Philos. Trans. R. Soc. Lond. B Biol. Sci. 2005, 360:1427-1434.
19. Felsenstein J. Comparative methods with sampling error and within-species variation: contrasts revisited and revised. Am. Nat. 2008, 171:713-725.
20. Fisher DO, Blomberg SP, Owens IPF. Extrinsic versus intrinsic factors in the decline and extinction of Australian marsupials. Proc. R. Soc. Lond. B Biol. Sci. 2003, 270:1801-1808.
21. Foulley JL, Gianola D, Thompson R. Prediction of genetic merit from data on binary and quantitative variates with an application to calving difficulty, birth-weight and pelvic opening. Genet. Sel. Evol. 1983, 15:401-423.
22. Freckleton RP, Harvey PH, Pagel M. Phylogenetic analysis and comparative data: a test and review of evidence. Am. Nat. 2002, 160:712-726.
23. Garcia-Cortes LA, Sorensen D. Alternative implementations of Monte Carlo EM algorithms for likelihood inferences. Genet. Sel. Evol. 2001, 33:443-452.
24. Garland T, Ives AR. Using the past to predict the present: confidence intervals for regression equations in phylogenetic comparative methods. Am. Nat. 2000, 155:346-364.
25. Gelman A, Carlin JB, Stern HS, Rubin DB. Bayesian Data Analysis. Texts in Statistical Science. 2004, Chapman & Hall, Boca Raton, 2nd edn
26. Geman S, Geman D. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEET. Pattern Anal 1984, 6:721-741.
27. Gianola D, Foulley JL. Sire evaluation for ordered categorical-data with a threshold-model. Genet. Sel. Evol. 1983, 15:201-223.
28. Gilmour AR, Gogel BJ, Cullis BR, Welham SJ, Thompson R. ASReml User Guide Release 1.0. 2002, http://www.VSN-Intl.com, [www document]. URL
29. Hadfield JD. Estimating evolutionary parameters when viability selection is operating. Proc. R. Soc. Biol. Sci. Ser. B 2008, 275:723-734.
30. Hadfield J. MCMC methods for multi-response generalised linear mixed models: The MCMCglmm R package. Journal of Statistical Software 2010
31. Hansen TF, Martins EP. Translating between microevolutionary process and macroevolutionary patterns: the correlation structure of interspecific data. Evolution 1996, 50:1404-1417.
32. Hastings WK. Monte-Carlo sampling methods using Markov chains and their applications. Biometrika 1970, 57:97-109.
33. Hedeker D. A mixed-effects multinomial logistic regression model. Stat. Med. 2003, 22:1433-1446.
34. Henderson CR. Simple method for computing inverse of a numerator relationship matrix used in prediction of breeding values. Biometrics 1976, 32:69-83.
35. Higgins JPT, Thompson SG, Spiegelhalter DJ. A re-evaluation of random-effects meta-analysis. J. R. Stat. Soc. Ser. A-Stat. Soc. 2009, 172:137-159.
36. Housworth EA, Martins EP, Lynch M. The phylogenetic mixed model. Am. Nat. 2004, 163:84-96.
37. Huelsenbeck JP, Nielsen R, Bollback JP. Stochastic mapping of morphological characters. Syst. Biol. 2003, 52:131-158.
38. Im S, Fernando RL, Gianola D. Likelihood inferences in animal breeding under selection - a missing-data theory view point. Genet. Sel. Evol. 1989, 21:399-414.
39. Ives AR, Zhu J. Statistics for correlated data: phylogenies, space, and time. Ecol. Appl. 2006, 16:20-32.
40. Ives AR, Midford PE, Garland T. Within-species variation and measurement error in phylogenetic comparative methods. Syst. Biol. 2007, 56:252-270.
41. Jennions MD, Moller AP. Relationships fade with time: a meta-analysis of temporal trends in publication in ecology and evolution. Proc. R. Soc. Lond. B Biol. Sci. 2002, 269:43-48.
42. Kingsolver JG, Gomulkiewicz R, Carter PA. Variation, selection and evolution of function-valued traits. Genetica 2001, 112:87-104.
43. Korsgaard IR, Lund MS, Sorensen D, Gianola D, Madsen P, Jensen J. Multivariate Bayesian analysis of Gaussian, right censored Gaussian, ordered categorical and binary traits using Gibbs sampling. Genet. Sel. Evol. 2003, 35:159-183.
44. Kulinskaya E, Morgenthaler S, Staudte RB. Meta Analysis: A Guide to Calibrating and Combining Statistical Evidence 2008, John Wiley, Chichester
45. Lapointe FJ, Garland T. A generalized permutation model for the analysis of cross-species data. J. Classif. 2001, 18:109-127.
46. Little RJA, Rubin DB. Statistical Analysis with Missing Data 2002, Wiley-Interscience, Hoboken, NJ, 2nd edn
47. Lush JL, Shrode RR. Changes in milk production with age and milking frequency. J. Dairy Sci 1950, 33:338-357.
48. Lynch M. Methods for the analysis of comparative data in evolutionary biology. Evolution 1991, 45:1065-1080.
49. Lynch M, Walsh B. Genetics and Analysis of Quantitative Traits 1998, Sinauer, Sunderland, MA
50. Macaskill P, Walter SD, Irwig L. A comparison of methods to detect publication bias in meta-analysis. Stat. Med. 2001, 20:641-654.
51. Martins EP. Phylogenies, spatial autoregression, and the comparative method: a computer simulation test. Evolution 1996, 50:1750-1765.
52. Martins EP, Hansen TF. Phylogenies and the comparative method: a general approach to incorporating phylogenetic information into the analysis of interspecific data. Am. Nat. 1997, 149:646-667.
53. Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E. Equation of state calculations by fast computing machines. J. Chem. Phys. 1953, 21:1087-1092.
54. Meuwissen THE, Luo Z. Computing inbreeding coefficients in large populations. Genet. Sel. Evol. 1992, 24:305-313.
55. Moller AP, Jennions MD. Testing and adjusting for publication bias. Trends Ecol. Evol. 2001, 16:580-586.
56. Nakagawa S, Freckleton RP. Missing inaction: the dangers of ignoring missing data. Trends Ecol. Evol. 2008, 23:592-596.
57. Naya H, Gianola D, Romero H, Urioste JI, Musto H. Inferring parameters shaping amino acid usage in prokaryotic genomes via Bayesian MCMC methods. Molecular Biology and Evolution 2006, 23:203-211.
58. O'Hara RB, Cano JM, Ovaskainen O, Teplitsky C, Alho JS. Bayesian approaches in evolutionary quantitative genetics. J. Evol. Biol. 2008, 21:949-957.
59. Orwin RG. A fail-safe n for effect size n meta-analysis. J. Educ. Stat. 1983, 8:157-159.
60. Pagel M. Detecting correlated evolution on phylogenies - a general-method for the comparative-analysis of discrete characters. Proc. R. Soc. Lond. B Biol. Sci. 1994, 255:37-45.
61. Pagel M. Inferring the historical patterns of biological evolution. Nature 1999, 401:877-884.
62. Pagel M, Meade A. Bayesian analysis of correlated evolution of discrete characters by reversible-jump Markov chain Monte Carlo. Am. Nat. 2006, 167:808-825.
63. Pagel M, Meade A, Barker D. Bayesian estimation of ancestral character states on phylogenies. Syst. Biol. 2004, 53:673-684.
64. Paradis E. Analysis of Phylogenetics and Evolution with R 2006, Springer-Verlag, New York
65. Patterson HD, Thompson R. Recovery of inter-block information when block sizes are unequal. Biometrika 1971, 58:545-554.
66. Quaas RL. Computing diagonal elements and inverse of a large numerator relationship matrix. Biometrics 1976, 32:949-953.
67. Rao JNK, Wu CFJ. Resampling inference with complex survey data. J. Am. Stat. Assoc. 1988, 83:231-241.
68. Revell LJ, Harmon LJ, Collar DC. Phylogenetic signal, evolutionary process, and rate. Syst. Biol. 2008, 57:591-601.
69. Roberts GO, Sahu SK. Updating schemes, correlation structure, blocking and parameterization for the Gibbs sampler. J. R. Stat. Soc. Ser. B-Stat. Methodol. 1997, 59:291-317.
70. Rosenberg MS. The file-drawer problem revisited: a general weighted method for calculating fail-safe numbers in meta-analysis. Evolution 2005, 59:464-468.
71. Rosenthal R. The ''file drawer problem'' and tolerance for null results. Psychol. Bull. 1979, 86:638-641.
72. Rothstein H, Sutton AJ, Borenstein M. Publication Bias in Meta-analysis: Prevention, Assessment and Adjustments 2005, eds, John Wiley, Chichester
73. Rubin DB. Inference and missing data. Biometrika 1976, 63:581-590.
74. Shao J, Tu S. The Jackknife and Bootstrap. Springer Series in Statistics 1996, Springer, New York
75. Smith D, Givens GH, Tweedie R. Adjusting for publication and quality bias in Bayesian meta-analysis. Meta-analysis in Medicine and Health Policy 2000, 277-304. Stangl D, Berry D, In, eds, pp, Marcel Dekker, New York
76. Sorensen D, Gianola D. Likelihood, Bayesian and MCMC Methods in Quantitative Genetics. Statistics for Biology and Health 2002, Springer-Verlag, New York
77. Sorensen DA, Andersen S, Gianola D, Korsgaard I. Bayesian-inference in threshold models using Gibbs sampling. Genet. Sel. Evol. 1995, 27:229-249.
78. Sterne JAC, Egger M. Regression method to detect publication and other bias in meta-analysis. Publication Bias in Meta-analysis: Prevention, Assessment and Adjustments 2005, 99-125. Rothstein H, Sutton AJBorenstein M. In, eds, pp, John Wiley, Chichester
79. Sterne JAC, Becker BJ, Egger M. The funnel plot. Publication Bias in Meta-analysis: Prevention, Assessment and Adjustments 2005, 75-98. Rothstein H, Sutton AJ, Borenstein M. In, eds, pp, John Wiley, Chichester
80. Tanner MA, Wong WH. The calculation of posterior distributions by data augmentation. J. Am. Stat. Assoc. 1987, 82:528-540.
81. Thompson R. Estimation of quantitative genetic parameters. Proc. R. Soc. Biol. Sci. Ser. B 2008, 275:679-686.
82. Thompson R, Brotherstone S, White IMS. Estimation of quantitative genetic parameters. Philos. Trans. R. Soc. Lond. B Biol. Sci. 2005, 360:1469-1477.
83. West SA, Sheldon BC. Constraints in the evolution of sex ratio adjustment. Science 2002, 295:1685-1688.
84. Wright S. An analysis of variability in number of digits in an inbred strain of guinea pigs. Genetics 1934a, 19:0506-0536.
85. Wright S. The results of crosses between inbred strains of guinea pigs, differing in number of digits. Genetics 1934b, 19:0537-0551.