How many bootstrap replicates are necessary?

Journal of Computational Biology

Volumn 17, Issue 3, 2010, Pages 337-354

  Pattengale, Nicholas D ^a   Alipour, Masoud ^a   Bininda Emonds, Olaf R P ^c   Moret, Bernard M E ^b,d   Stamatakis, Alexandros ^e  

^a University of New Mexico   (United States)

^b EPFL   (Switzerland)

^c UNIVERSITY OF OLDENBURG   (Germany)

^d SWISS INSTITUTE OF BIOINFORMATICS   (Switzerland)

^e TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

Bootstopping; Bootstrap; Maximum likelihood; Phylogenetic inference; Stopping criterion; Support value

Indexed keywords

BIOLOGY; CONFERENCE PAPER; CONFIDENCE INTERVAL; GENETIC DATABASE; METHODOLOGY; PHYLOGENY; REPRODUCIBILITY; STATISTICAL MODEL; TIME;

COMPUTATIONAL BIOLOGY; CONFIDENCE INTERVALS; DATABASES, GENETIC; LIKELIHOOD FUNCTIONS; PHYLOGENY; REPRODUCIBILITY OF RESULTS; TIME FACTORS;

EID: 77950820827     PISSN: 10665277     EISSN: None     Source Type: Journal    
DOI: 10.1089/cmb.2009.0179     Document Type: Conference Paper

References (47)

1. Aberer, A., Pattengale, N., and Stamatakis, A. 2010. Parallel Computation of Phylogenetic Consensus Trees. Exelixis-RRDR-2010-2011 TU Munich, January 2010. Submitted.
2. Amenta, N., Clarke, F., and St. John, K. 2003. A linear-time majority tree algorithm. Lect. Notes Comput. Sci. 216-227. (Pubitemid 37171422)
3. Andrews, D.W.K., and Buchinsky, M. 1997. On the Number of Bootstrap Repetitions for Bootstrap Standard Errors, Confidence Intervals, and Tests. Cowles Foundation Paper 1141R.
4. Andrews, D.W.K., and Buchinsky, M. 2000. A three-step method for choosing the number of bootstrap repetitions. Econometrica 68, 23-51.
5. Andrews, D.W.K., and Buchinsky, M. 2001. Evaluation of a three-step method for choosing the number of bootstrap repetitions. J. Econometrics 103, 345-386. (Pubitemid 33645276)
6. Andrews, D.W.K., and Buchinsky, M. 2002. On the number of bootstrap repetitions for BCA confidence intervals. Econometric Theory 18, 962-984. (Pubitemid 36399937)
7. Brooks, S.P., and Gelman, A. 1998. General methods for monitoring convergence of iterative simulations. J. Comput. Graphical Statist. 7, 434-455. (Pubitemid 128635035)
8. Carter, J.L., and Wegman, M.N. 1977. Universal classes of hash functions. Proc. 9th Annu. ACM Symp. Theory Comput. 106-112.
9. Davidson, A.C., and Hinkley, D.V. 2003. Bootstrap Methods and Their Application. Cambridge University Press, New York.
10. Davidson, R., and MacKinnon, J.G. 2000. Bootstrap tests: how many bootstraps? Econometric Rev. 19, 55-68.
11. Day, W.H.E. 1985. Optimal algorithms for comparing trees with labeled leaves. J. Classif. 2, 7-28.
12. Edwards, A.W.F., Cavalli-Sforza, L.L., Heywood, V.H., et al. 1963. Phenetic and phylogenetic classification. System. Assoc. Public. 6, 67-76.
13. Efron, B., and Tibshirani, R.J. 1993. An Introduction to the Bootstrap. Chapman & Hall, New York.
14. Felsenstein, J. 1985. Confidence limits on phylogenies: an approach using the bootstrap. Evolution 39, 783-791.
15. Felsenstein, J. 1981. Evolutionary trees from DNA sequences: a maximum likelihood approach. J. Mol. Evol. 17, 368-376. (Pubitemid 11016207)
16. Foulds, L.R., and Graham, R.L. 1982. The Steiner problem in phylogeny is NP-complete. Adv. Appl. Math. 3, 299.
17. Gelman, A., and Rubin, D.B. 1992. Inference from iterative simulation using multiple sequences. Statist Sci. 7, 457-511.
18. Grimm, G.W., Renner, S.S., Stamatakis, A., et al. 2006. A nuclear ribosomal DNA phylogeny of acer inferred with maximum likelihood, splits graphs, and motif analyses of 606 sequences. Evol. Bioinform. Online 2, 279-294.
19. Guindon, S., and Gascuel, O. 2003. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52, 696-704. (Pubitemid 37365050)
20. Guo, W., and Peddada, S. 2008. Adaptive choice of the number of bootstrap samples in large-scale multiple testing. Statist Appl. Genet. Mol. Biol. 7, 1.
21. Hall, P. 1986. On the number of bootstrap simulations required to construct a confidence interval. Ann. Statist. 14, 1453-1462.
22. Hedges, S.B. 1992. The number of replications needed for accurate estimation of the bootstrap P value in phylogenetic studies. Mol. Biol. Evol. 9, 366-369.
23. Hejnol, A., Obst, M., Stamatakis, A., et al. 2009. Assessing the root of bilaterian animals with scalable phylogenomic methods. In: Proc. R. Soc. B276, 4261-4270.
24. Hillis, D.M., and Bull, J.J. 1993. An empirical test of bootstrapping as a method for assessing confidence in phylogenetic analysis. System. Biol. 42, 182.
25. Holmes, S. 2003. Bootstrapping phylogenetic trees: theory and methods. Statist. Sci. 18, 241-255. (Pubitemid 37545097)
26. Jermiin, L.S., Olsen, G.J., Mengerson, K.L., et al. 1997. Majority-rule consensus of phylogenetic trees obtained by maximum-likelihood analysis. Mol. Biol. Evol. 14, 1296.
27. Manly, B.F.J. 1997. Randomization, Bootstrap and Monte Carlo Methods in Biology. CRC Press, Boca Raton, FL.
28. Moret, B.M.E. 2007. Large-scale phylogenetic reconstruction, 29-48. In: Brown, J.R., ed., Comparative Genomics: Basic and Applied Research, CRC Press/Taylor & Francis, Boca Raton, FL.
29. Moret, B.M.E. 2002. Towards a discipline of experimental algorithmics, 197. In: Data Structures, Near Neighbor Searches, and Methodology: Fifth and Sixth DIMACS Implementation Challenges: Papers Related to the DIMACS Challenge on Dictionaries and Priority Queues (1995-1996) and the DIMACS Challenge on Near Neighbor Searches (1998-1999).
30. Mossel, E., and Vigoda, E. 2006. Limitations of Markov chain Monte Carlo algorithms for Bayesian inference of phylogeny. Ann. Appl. Probab. 16, 2215-2234.
31. Nylander, J.A.A., Wilgenbusch, J.C., Warren, D.L., et al. 2007. AWTY (Are We There Yet?): a system for graphical exploration of MCMC convergence in Bayesian phylogenetics. Bioinformatics advance access August 30.
32. Pattengale, N.D., Gottlieb, E.J., and Moret, B.M.E. 2007. Efficiently computing the Robinson-Foulds metric. J. Comput. Biol. 14, 724-735.
33. Pattengale, N.D., Alipour, M., Bininda-Emonds, O.R.P., et al. 2009. How many bootstrap replicates are necessary? Lect. Notes Comput. Sci. 5541, 184-200.
34. Rambaut, A., and Drummond, A. 2004. Tracer MCMC Trace Analysis Tool, version 1.3.
35. Robinson, D.F., and Foulds, L.R. 1981. Comparison of phylogenetic trees. Math. Biosci., 53, 131-147.
36. Roch, S. 2006. A short proof that phylogenetic tree reconstruction by maximum likelihood is hard. IEEE/ACM Trans. Comput. Biol. Bioinform. 92-94. (Pubitemid 43269830)
37. Ronquist, F., and Huelsenbeck, J.P. 2003. MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19, 1572-1574. (Pubitemid 37038874)
38. Soltis, D.E., and Soltis, P.S. 2003. Applying the bootstrap in phylogeny reconstruction. Statist. Sci. 18, 256-267.
39. Soltis, D.E., Gitzendanner, M.A., and Soltis, P.S. 2007. A 567-taxon data set for angiosperms: the challenges posed by Bayesian analyses of large data sets. Int. J. Plant Sci. 168, 137-157. (Pubitemid 46311062)
40. Stamatakis, A. 2006. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 22, 2688-2690. (Pubitemid 44642609)
41. Stamatakis, A., and Ott, M. 2008. Efficient computation of the phylogenetic likelihood function on multi-gene alignments and multi-core architectures. Phil. Trans. R. Soc. B, 363, 3977-3984.
42. Stamatakis, A., Meier, H., and Ludwig, T. 2004. New fast and accurate heuristics for inference of large phylogenetic trees. Proc. IPDPS2004. (Pubitemid 40142254)
43. Stamatakis, A., Hoover, P., and Rougemont. 2008. A rapid bootstrap algorithm for the RAxML web servers. System Biol. (in press).
44. Sul, S.J., and Williams, T.L. 2007. A randomized algorithm for comparing sets of phylogenetic trees. Proc. 5th Asia-Pacific Bioinform. Conf. 121.
45. Sul, S.J., Brammer, G., and Williams, T.L. 2008. Efficiently computing arbitrarily-sized Robinson-Foulds distance matrices. Proc. 8th Int. Workshop Algorithms Bioinform. 123-134.
46. Whelan, S. 2007. New approaches to phylogenetic tree search and their application to large numbers of protein alignments. Syst. Biol. 56, 727-740. (Pubitemid 47402906)
47. Zwickl, D. 2006. Genetic Algorithm Approaches for the Phylogenetic Analysis of Large Biological Sequence Datasets under the Maximum Likelihood Criterion. [Ph.D. dissertation]. University of Texas at Austin.