Bootstrapping - Revision history

Christoph at 04:52, 13 September 2006

2006-09-13T04:52:52Z

Christoph: Added more refs.

2005-12-31T02:43:16Z

Added more refs.

Christoph: /* References */ Added more refs.

2005-12-31T02:19:26Z

‎References: Added more refs.

Christoph: Added "Conventions"

2005-12-31T01:46:50Z

Added "Conventions"

Christoph: Started article

2005-12-31T01:27:09Z

Started article

New page

'''Bootstrapping''', when applied to [[phylogenetics]], tests whether your entire dataset is supporting your phylogenetic tree, or if the tree is just a marginal winner among many nearly equal alternatives.

<blockquote>"[Bootstrapping is accomplished] by taking random subsamples of the dataset, building trees from each of these and calculating the frequency with which the various parts of your tree are reproduced in each of these random subsamples. If group X is found in every subsample tree, then its bootstrap support is 100%; if it is found in only two-thirds of the subsample trees, its bootstrap support is 67%. Each of the subsamples is the same size as the original, which is accomplished by allowing repeat sampling of sites; that is, random sampling with replacement. It is a simple test, but bootstrap analyses of known phylogenies (viral populations evolved in the laboratory) show that is is a generally dependable measure of phylogenetic accuracy, and that values of 70% or higher are likely to indicate reliable groupings." — by Sandra L. Baldauf (2003).
</blockquote>

== Statistics ==
In [[statistics]] bootstrapping is a method for estimating the sampling distribution of an estimator by resampling with replacement from the original sample. It is distinguished from the jackknife procedure, used to detect outliers, and cross-validation, whose purpose is to make sure that results are repeatable. There are more complicated bootstraps for sampling without replacement, two-sample problems, regression, time series, hierarchical sampling, and other statistical problems.

See also particle filter for the general theory of ''Sequential Monte Carlo'' methods, as well as details on some common implementations.

== References ==
=== Phylogenetics ===
* Baldauf SL (2003). Phylogeny for the faint of heart: a tutorial. ''TRENDS in Genetics'' '''19(6)''':345-351.
* Hillis DM and Bull JJ (1993). An empirical test of bootstrapping as a method for assessing confidence in phylogenetic analyses. ''Sys Biol'' '''42''':182-192.
* Felsenstein J (1985). Confidence limits on phylogenies: an approach using the bootstrap. ''Evolution'' '''39''':783-791.
=== Statistics ===
* Hesterberg TC, Moore DS, Monaghan S, Clipson A, and Epstein R (2005). [http://bcs.whfreeman.com/ips5e/content/cat_080/pdf/moore14.pdf Bootstrap Methods and Permutation Tests] ([http://www.insightful.com/Hesterberg/bootstrap software]).
* Moore DS, McCabe G, Duckworth W, and Sclove S (2003). [http://bcs.whfreeman.com/pbs/cat_140/chap18.pdf Bootstrap Methods and Permutation Tests].
* Simon JL (1997). [http://www.resample.com/content/text/index.shtml Resampling: The New Statistics].

[[Category:Academic Research]]
[[Category:Phylogenetics]]
[[Category:Statistics]]

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 <blockquote>"[Bootstrapping is accomplished] by taking random subsamples of the dataset, building trees from each of these and calculating the frequency with which the various parts of your tree are reproduced in each of these random subsamples. If group X is found in every subsample tree, then its bootstrap support is 100%; if it is found in only two-thirds of the subsample trees, its bootstrap support is 67%. Each of the subsamples is the same size as the original, which is accomplished by allowing repeat sampling of sites; that is, random sampling with replacement. It is a simple test, but bootstrap analyses of known phylogenies (viral populations evolved in the laboratory) show that is is a generally dependable measure of phylogenetic accuracy, and that values of 70% or higher are likely to indicate reliable groupings." &mdash; by Sandra L. Baldauf (2003).
 </blockquote>
 == Statistics ==
@@ Line 19: / Line 26: @@
 * Baldauf SL (2003). Phylogeny for the faint of heart: a tutorial. ''TRENDS in Genetics'' '''19(6)''':345-351.
 * Efron B, Halloran E, and Holmes S (1996). Bootstrap confidence levels for phylogenetic trees. ''Proc Natl Acad Sci USA'' '''93''':13429-13434.
 * Efron B and Tibshirani RJ (1993). ''An Introduction to the Bootstrap''. Chapman and Hall (New York).
 * Hillis DM and Bull JJ (1993). An empirical test of bootstrapping as a method for assessing confidence in phylogenetic analyses. ''Sys Biol'' '''42''':182-192.
 * Felsenstein J and Kishino H (1993). Is there something wrong with the bootstrap on phylogenies? A reply to Hillis and Bull. ''Syst Biol'' '''42''':193–200.
 * Goldman N (1993). Statistical tests of models of DNA substitution. ''J Mol Evol'' '''36''':182–198.
 * Felsenstein J (1985). Confidence limits on phylogenies: an approach using the bootstrap. ''Evolution'' '''39''':783-791.
 === Statistics ===

← Older revision		Revision as of 01:46, 31 December 2005
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	See also particle filter for the general theory of ''Sequential Monte Carlo'' methods, as well as details on some common implementations.		See also particle filter for the general theory of ''Sequential Monte Carlo'' methods, as well as details on some common implementations.
		+
		+	== Conventions ==
		+	Bootstrap values should be displayed as percentages, not raw values. This makes the tree easier to read and to compare with other trees (Baldauf, 2003).
		+
		+	By convention, only bootstrap values of 50% or higher are reported; lower values mean that the node in question was found in less than half of the bootstrap replicates (Baldauf, 2003).

	== References ==		== References ==

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 * Simon JL (1997). [http://www.resample.com/content/text/index.shtml Resampling: The New Statistics].
-[[Category:Academic Research]]
+{{Phylogenetics}}
 [[Category:Phylogenetics]]