https://www.r-phylo.org/w/index.php?title=Available_Packages_and_Analyses&feed=atom&action=historyAvailable Packages and Analyses - Revision history2024-03-28T10:56:56ZRevision history for this page on the wikiMediaWiki 1.41.0https://www.r-phylo.org/w/index.php?title=Available_Packages_and_Analyses&diff=635&oldid=prevHilmar: /* Packages and Analyses available in R */2009-08-27T20:35:03Z<p><span dir="auto"><span class="autocomment">Packages and Analyses available in R</span></span></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 16:35, 27 August 2009</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Ancestral state reconstruction''' : Continuous characters can be reconstructed using maximum likelihood, generalised least squares or independent contrasts in <span style="color: green"> ape </span>. Root ancestral character states under Brownian motion or Ornstein-Uhlenbeck models can be reconstructed in <span style="color: green"> OUCH </span>, though ancestral states at the internal nodes are not. Discrete characters can be reconstructed using a variety of Markovian models that parameterize the transition rates among states using <span style="color: green"> ape </span>.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Ancestral state reconstruction''' : Continuous characters can be reconstructed using maximum likelihood, generalised least squares or independent contrasts in <span style="color: green"> ape </span>. Root ancestral character states under Brownian motion or Ornstein-Uhlenbeck models can be reconstructed in <span style="color: green"> OUCH </span>, though ancestral states at the internal nodes are not. Discrete characters can be reconstructed using a variety of Markovian models that parameterize the transition rates among states using <span style="color: green"> ape </span>.</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>'''Diversification Analysis''': Lineage through time plots can be done in <span style="color: green"> ape </span>and <span style="color: green"> laser </span>. A simple birth-death model for when you have extant species only (sensu Nee et al. 1994) can be fitted in <span style="color: green"> ape </span> as can survival models and goodness-of-fit tests (as applied to testing of models of diversification). <span style="color: green"> Laser</span> implements likelihood methods using a model testing approach for inferring temporal shifts in diversification rates based on a birth-death or pure-birth process. The gamma statistic (Pybus and Harvey 2000) is also available in <span style="color: green"> laser</span>. Colless and Sackin's topological methods for analyzing diversification are available in <span style="color: green"> apTreeshape </span> as is the test for significant shifts in diversification (sensu Moore, Chan and Donoghue 2004). Net rates of diversification (sensu Magellon and Sanderson) can be calculated in <span style="color: green"> geiger </span>.</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>'''Diversification Analysis''': Lineage through time plots can be done in <span style="color: green"> ape </span>and <span style="color: green"> laser </span>. A simple birth-death model for when you have extant species only (sensu Nee et al. 1994) can be fitted in <span style="color: green"> ape </span> as can survival models and goodness-of-fit tests (as applied to testing of models of diversification). <span style="color: green"> Laser</span> implements likelihood methods using a model testing approach for inferring temporal shifts in diversification rates based on a birth-death or pure-birth process. The gamma statistic (Pybus and Harvey 2000) is also available in <span style="color: green"> laser</span>. Colless and Sackin's topological methods for analyzing diversification are available in <span style="color: green"> apTreeshape </span> as is the test for significant shifts in diversification (sensu Moore, Chan and Donoghue 2004). Net rates of diversification (sensu Magellon and Sanderson) can be calculated in <span style="color: green"> geiger </span><ins style="font-weight: bold; text-decoration: none;">. The <span style="color: green"> diversitree </span> package includes the BiSSE method (Binary State Speciation and Extinction; Maddison et al. 2007) and extensions for terminally unresolved trees and skeleton trees (FitzJohn et al., Syst. Biol., in press)</ins>.</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Divergence Times''': Non-parametric rate smoothing (NPRS) and penalized likelihood can be implemented in <span style="color: green"> ape </span>.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Divergence Times''': Non-parametric rate smoothing (NPRS) and penalized likelihood can be implemented in <span style="color: green"> ape </span>.</div></td></tr>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Tree Simulations''': Trees can be simulated using a Yule, PDA, biased or speciation specified model in apTreeshape, a birth-death process in <span style="color: green"> geiger </span>, and <span style="color: green"> PhySim </span>. Random trees can be generated in <span style="color: green"> ape </span> by random splitting of edges (for non-parametric trees) or random clustering of tips (for coalescent trees).</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Tree Simulations''': Trees can be simulated using a Yule, PDA, biased or speciation specified model in apTreeshape, a birth-death process in <span style="color: green"> geiger </span>, and <span style="color: green"> PhySim </span>. Random trees can be generated in <span style="color: green"> ape </span> by random splitting of edges (for non-parametric trees) or random clustering of tips (for coalescent trees).</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>'''Trait evolution''': Independent contrasts for continuous characters can be calculated using <span style="color: green"> ape </span>. Pagel's continuous and discrete analyzes can be calculated in <span style="color: green"> geiger </span>. Ornstein-Uhlenbeck (OU) models can be fitted in <span style="color: green"> geiger</span>, <span style="color: green"> ape</span> and <span style="color: green"> OUCH</span>. In its current implementation, <span style="color: green"> geiger</span> fits only single-optimum models. <span style="color: green"> Matticce </span> implements an information-theoretic approach to estimating where transitions in a continuous character have occurred on a phylogenetic tree, provides helper functions for <span style="color: green"> OUCH</span> to automate the process of painting regimes and to summarize analyses over trees and over regimes, and provides a simulation functions for visualizing how different model parameters affect inference of the evolution of a continuous character. ANOVA's and MANOVA's in a phylogenetic context can also be implemented in <span style="color: green"> geiger</span>. A GLS linear model (sensu Garland and Ives 2000) can be fitted using <span style="color: green"> PHYLOGR</span>; the more traditional GLS methods (senu Grafen or Martins) can be implemented in <span style="color: green"> ape</span>. Phylogenetic autoregression (sensu Cheverud et al) and Phylogenetic autocorrelation (Moran's I) can be implemented in <span style="color: green"> ape </span> or--if you wish the significance test of Moran's I to be calculated via a randomization procedure--in <span style="color: green"> ade4 </span>. The package <span style="color: green"> smatr </span> fits bivariate lines in allometry using the major axis (MA) or standardised major axis (SMA), and allows to make inferences about such lines, including confidence intervals, one-sample tests for slope and elevation, and testing for a common slope or elevation amongst several allometric lines. </div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>'''Trait evolution''': Independent contrasts for continuous characters can be calculated using <span style="color: green"> ape </span>. Pagel's continuous and discrete analyzes can be calculated in <span style="color: green"> geiger </span>. Ornstein-Uhlenbeck (OU) models can be fitted in <span style="color: green"> geiger</span>, <span style="color: green"> ape</span> and <span style="color: green"> OUCH</span>. In its current implementation, <span style="color: green"> geiger</span> fits only single-optimum models. <span style="color: green"> Matticce </span> implements an information-theoretic approach to estimating where transitions in a continuous character have occurred on a phylogenetic tree, provides helper functions for <span style="color: green"> OUCH</span> to automate the process of painting regimes and to summarize analyses over trees and over regimes, and provides a simulation functions for visualizing how different model parameters affect inference of the evolution of a continuous character. ANOVA's and MANOVA's in a phylogenetic context can also be implemented in <span style="color: green"> geiger</span>. A GLS linear model (sensu Garland and Ives 2000) can be fitted using <span style="color: green"> PHYLOGR</span>; the more traditional GLS methods (senu Grafen or Martins) can be implemented in <span style="color: green"> ape</span>. Phylogenetic autoregression (sensu Cheverud et al) and Phylogenetic autocorrelation (Moran's I) can be implemented in <span style="color: green"> ape </span> or--if you wish the significance test of Moran's I to be calculated via a randomization procedure--in <span style="color: green"> ade4 </span>. The package <span style="color: green"> smatr </span> fits bivariate lines in allometry using the major axis (MA) or standardised major axis (SMA), and allows to make inferences about such lines, including confidence intervals, one-sample tests for slope and elevation, and testing for a common slope or elevation amongst several allometric lines.</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Trait Simulations''' : Continuous traits can be simulated using brownian motion in <span style="color: green"> OUCH </span> and <span style="color: green"> geiger </span>, the Hansen model in <span style="color: green"> OUCH </span> and a speciational model in <span style="color: green"> geiger </span>. Discrete traits can be simulated using a continuous time Markov model in <span style="color: green"> geiger </span>. Both discrete and continuous traits can be simulated under models where rates change through time in <span style="color: green"> geiger </span>.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Trait Simulations''' : Continuous traits can be simulated using brownian motion in <span style="color: green"> OUCH </span> and <span style="color: green"> geiger </span>, the Hansen model in <span style="color: green"> OUCH </span> and a speciational model in <span style="color: green"> geiger </span>. Discrete traits can be simulated using a continuous time Markov model in <span style="color: green"> geiger </span>. Both discrete and continuous traits can be simulated under models where rates change through time in <span style="color: green"> geiger </span>.</div></td></tr>
</table>Hilmarhttps://www.r-phylo.org/w/index.php?title=Available_Packages_and_Analyses&diff=634&oldid=prevHilmar: /* Packages not yet on CRAN */2009-08-27T20:26:27Z<p><span dir="auto"><span class="autocomment">Packages not yet on CRAN</span></span></p>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [http://www.zoology.ubc.ca/prog/diversitree/ Diversitree]</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [http://r-forge.r-project.org/projects/mattice/ maticce]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [http://r-forge.r-project.org/projects/mattice/ maticce]</div></td></tr>
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</table>Hilmarhttps://www.r-phylo.org/w/index.php?title=Available_Packages_and_Analyses&diff=633&oldid=prevHilmar: /* References */2009-01-23T20:24:31Z<p><span dir="auto"><span class="autocomment">References</span></span></p>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Pagel M 1999 Inferring the historical patterns of biological evolution. Nature 401, 877-884</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Pagel M 1999 Inferring the historical patterns of biological evolution. Nature 401, 877-884</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Pybus OG, Harvey PH 2000. Testing macro-evolutionary models using incomplete molecular phylogenies. Proceedings of the Royal Society of London Series B Biological Sciences 267, 2267-2272.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Pybus OG, Harvey PH 2000. Testing macro-evolutionary models using incomplete molecular phylogenies. Proceedings of the Royal Society of London Series B Biological Sciences 267, 2267-2272.</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Warton, David I., Ian J. Wright, Daniel S. Falster and Mark Westoby (2006). Bivariate line-fitting methods for allometry. Biological Reviews 81: 259-291</ins></div></td></tr>
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<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">[[Category:HowTo]][[Category:R Help]]</del>[[Category:Comparative Methods Help]]</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[[Category:Comparative Methods Help]]</div></td></tr>
</table>Hilmarhttps://www.r-phylo.org/w/index.php?title=Available_Packages_and_Analyses&diff=632&oldid=prevHilmar: /* Packages on CRAN */2009-01-23T20:23:21Z<p><span dir="auto"><span class="autocomment">Packages on CRAN</span></span></p>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [http://cran.r-project.org/web/packages/PhySim/index.html PhySim]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [http://cran.r-project.org/web/packages/PhySim/index.html PhySim]</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [http://cran.r-project.org/web/packages/picante/index.html picante]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [http://cran.r-project.org/web/packages/picante/index.html picante]</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [http://cran.r-project.org/web/packages/psmatr/index.html smatr]</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Packages not yet on CRAN ===</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Packages not yet on CRAN ===</div></td></tr>
</table>Hilmarhttps://www.r-phylo.org/w/index.php?title=Available_Packages_and_Analyses&diff=631&oldid=prevHilmar: /* Packages and Analyses available in R */2009-01-23T20:22:41Z<p><span dir="auto"><span class="autocomment">Packages and Analyses available in R</span></span></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
<col class="diff-marker" />
<col class="diff-content" />
<col class="diff-marker" />
<col class="diff-content" />
<tr class="diff-title" lang="en">
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 16:22, 23 January 2009</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l15">Line 15:</td>
<td colspan="2" class="diff-lineno">Line 15:</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Tree Simulations''': Trees can be simulated using a Yule, PDA, biased or speciation specified model in apTreeshape, a birth-death process in <span style="color: green"> geiger </span>, and <span style="color: green"> PhySim </span>. Random trees can be generated in <span style="color: green"> ape </span> by random splitting of edges (for non-parametric trees) or random clustering of tips (for coalescent trees).</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Tree Simulations''': Trees can be simulated using a Yule, PDA, biased or speciation specified model in apTreeshape, a birth-death process in <span style="color: green"> geiger </span>, and <span style="color: green"> PhySim </span>. Random trees can be generated in <span style="color: green"> ape </span> by random splitting of edges (for non-parametric trees) or random clustering of tips (for coalescent trees).</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>'''Trait evolution''': Independent contrasts for continuous characters can be calculated using <span style="color: green"> ape </span>. Pagel's continuous and discrete analyzes can be calculated in <span style="color: green"> geiger </span>. Ornstein-Uhlenbeck (OU) models can be fitted in <span style="color: green"> geiger</span>, <span style="color: green"> ape</span> and <span style="color: green"> OUCH</span>. In its current implementation, <span style="color: green"> geiger</span> fits only single-optimum models. <span style="color: green"> Matticce </span> implements an information-theoretic approach to estimating where transitions in a continuous character have occurred on a phylogenetic tree, provides helper functions for <span style="color: green"> OUCH</span> to automate the process of painting regimes and to summarize analyses over trees and over regimes, and provides a simulation functions for visualizing how different model parameters affect inference of the evolution of a continuous character. ANOVA's and MANOVA's in a phylogenetic context can also be implemented in <span style="color: green"> geiger</span>. A GLS linear model (sensu Garland and Ives 2000) can be fitted using <span style="color: green"> PHYLOGR</span>; the more traditional GLS methods (senu Grafen or Martins) can be implemented in <span style="color: green"> ape</span>. Phylogenetic autoregression (sensu Cheverud et al) and Phylogenetic autocorrelation (Moran's I) can be implemented in <span style="color: green"> ape </span> or--if you wish the significance test of Moran's I to be calculated via a randomization procedure--in <span style="color: green"> ade4 </span>.</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>'''Trait evolution''': Independent contrasts for continuous characters can be calculated using <span style="color: green"> ape </span>. Pagel's continuous and discrete analyzes can be calculated in <span style="color: green"> geiger </span>. Ornstein-Uhlenbeck (OU) models can be fitted in <span style="color: green"> geiger</span>, <span style="color: green"> ape</span> and <span style="color: green"> OUCH</span>. In its current implementation, <span style="color: green"> geiger</span> fits only single-optimum models. <span style="color: green"> Matticce </span> implements an information-theoretic approach to estimating where transitions in a continuous character have occurred on a phylogenetic tree, provides helper functions for <span style="color: green"> OUCH</span> to automate the process of painting regimes and to summarize analyses over trees and over regimes, and provides a simulation functions for visualizing how different model parameters affect inference of the evolution of a continuous character. ANOVA's and MANOVA's in a phylogenetic context can also be implemented in <span style="color: green"> geiger</span>. A GLS linear model (sensu Garland and Ives 2000) can be fitted using <span style="color: green"> PHYLOGR</span>; the more traditional GLS methods (senu Grafen or Martins) can be implemented in <span style="color: green"> ape</span>. Phylogenetic autoregression (sensu Cheverud et al) and Phylogenetic autocorrelation (Moran's I) can be implemented in <span style="color: green"> ape </span> or--if you wish the significance test of Moran's I to be calculated via a randomization procedure--in <span style="color: green"> ade4 </span><ins style="font-weight: bold; text-decoration: none;">. The package <span style="color: green"> smatr </span> fits bivariate lines in allometry using the major axis (MA) or standardised major axis (SMA), and allows to make inferences about such lines, including confidence intervals, one-sample tests for slope and elevation, and testing for a common slope or elevation amongst several allometric lines</ins>. </div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Trait Simulations''' : Continuous traits can be simulated using brownian motion in <span style="color: green"> OUCH </span> and <span style="color: green"> geiger </span>, the Hansen model in <span style="color: green"> OUCH </span> and a speciational model in <span style="color: green"> geiger </span>. Discrete traits can be simulated using a continuous time Markov model in <span style="color: green"> geiger </span>. Both discrete and continuous traits can be simulated under models where rates change through time in <span style="color: green"> geiger </span>.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Trait Simulations''' : Continuous traits can be simulated using brownian motion in <span style="color: green"> OUCH </span> and <span style="color: green"> geiger </span>, the Hansen model in <span style="color: green"> OUCH </span> and a speciational model in <span style="color: green"> geiger </span>. Discrete traits can be simulated using a continuous time Markov model in <span style="color: green"> geiger </span>. Both discrete and continuous traits can be simulated under models where rates change through time in <span style="color: green"> geiger </span>.</div></td></tr>
</table>Hilmarhttps://www.r-phylo.org/w/index.php?title=Available_Packages_and_Analyses&diff=630&oldid=prevHilmar: /* Packages and Analyses available in R */2009-01-16T18:58:05Z<p><span dir="auto"><span class="autocomment">Packages and Analyses available in R</span></span></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
<col class="diff-marker" />
<col class="diff-content" />
<col class="diff-marker" />
<col class="diff-content" />
<tr class="diff-title" lang="en">
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 14:58, 16 January 2009</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l15">Line 15:</td>
<td colspan="2" class="diff-lineno">Line 15:</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Tree Simulations''': Trees can be simulated using a Yule, PDA, biased or speciation specified model in apTreeshape, a birth-death process in <span style="color: green"> geiger </span>, and <span style="color: green"> PhySim </span>. Random trees can be generated in <span style="color: green"> ape </span> by random splitting of edges (for non-parametric trees) or random clustering of tips (for coalescent trees).</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Tree Simulations''': Trees can be simulated using a Yule, PDA, biased or speciation specified model in apTreeshape, a birth-death process in <span style="color: green"> geiger </span>, and <span style="color: green"> PhySim </span>. Random trees can be generated in <span style="color: green"> ape </span> by random splitting of edges (for non-parametric trees) or random clustering of tips (for coalescent trees).</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>'''Trait evolution''': Independent contrasts for continuous characters can be calculated using ape. Pagel's continuous and discrete analyzes can be calculated in <span style="color: green"> geiger </span>. Ornstein-Uhlenbeck (OU) models can be fitted in <span style="color: green"> geiger</span>, <span style="color: green"> ape</span> and <span style="color: green"> OUCH</span>. In its current implementation, <span style="color: green"> geiger</span> fits only single-optimum models. ANOVA's and MANOVA's in a phylogenetic context can also be implemented in <span style="color: green"> geiger</span>. A GLS linear model (sensu Garland and Ives 2000) can be fitted using <span style="color: green"> PHYLOGR</span>; the more traditional GLS methods (senu Grafen or Martins) can be implemented in <span style="color: green"> ape</span>. Phylogenetic autoregression (sensu Cheverud et al) and Phylogenetic autocorrelation (Moran's I) can be implemented in <span style="color: green"> ape </span> or--if you wish the significance test of Moran's I to be calculated via a randomization procedure--in <span style="color: green"> ade4 </span>.</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>'''Trait evolution''': Independent contrasts for continuous characters can be calculated using <ins style="font-weight: bold; text-decoration: none;"><span style="color: green"> </ins>ape <ins style="font-weight: bold; text-decoration: none;"></span></ins>. Pagel's continuous and discrete analyzes can be calculated in <span style="color: green"> geiger </span>. Ornstein-Uhlenbeck (OU) models can be fitted in <span style="color: green"> geiger</span>, <span style="color: green"> ape</span> and <span style="color: green"> OUCH</span>. In its current implementation, <span style="color: green"> geiger</span> fits only single-optimum models<ins style="font-weight: bold; text-decoration: none;">. <span style="color: green"> Matticce </span> implements an information-theoretic approach to estimating where transitions in a continuous character have occurred on a phylogenetic tree, provides helper functions for <span style="color: green"> OUCH</span> to automate the process of painting regimes and to summarize analyses over trees and over regimes, and provides a simulation functions for visualizing how different model parameters affect inference of the evolution of a continuous character</ins>. ANOVA's and MANOVA's in a phylogenetic context can also be implemented in <span style="color: green"> geiger</span>. A GLS linear model (sensu Garland and Ives 2000) can be fitted using <span style="color: green"> PHYLOGR</span>; the more traditional GLS methods (senu Grafen or Martins) can be implemented in <span style="color: green"> ape</span>. Phylogenetic autoregression (sensu Cheverud et al) and Phylogenetic autocorrelation (Moran's I) can be implemented in <span style="color: green"> ape </span> or--if you wish the significance test of Moran's I to be calculated via a randomization procedure--in <span style="color: green"> ade4 </span>.</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Trait Simulations''' : Continuous traits can be simulated using brownian motion in <span style="color: green"> OUCH </span> and <span style="color: green"> geiger </span>, the Hansen model in <span style="color: green"> OUCH </span> and a speciational model in <span style="color: green"> geiger </span>. Discrete traits can be simulated using a continuous time Markov model in <span style="color: green"> geiger </span>. Both discrete and continuous traits can be simulated under models where rates change through time in <span style="color: green"> geiger </span>.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Trait Simulations''' : Continuous traits can be simulated using brownian motion in <span style="color: green"> OUCH </span> and <span style="color: green"> geiger </span>, the Hansen model in <span style="color: green"> OUCH </span> and a speciational model in <span style="color: green"> geiger </span>. Discrete traits can be simulated using a continuous time Markov model in <span style="color: green"> geiger </span>. Both discrete and continuous traits can be simulated under models where rates change through time in <span style="color: green"> geiger </span>.</div></td></tr>
</table>Hilmarhttps://www.r-phylo.org/w/index.php?title=Available_Packages_and_Analyses&diff=629&oldid=prevHilmar: /* CRAN packages */2009-01-16T18:50:24Z<p><span dir="auto"><span class="autocomment">CRAN packages</span></span></p>
<p><b>New page</b></p><div>==Packages and Analyses available in R==<br />
<br />
The history of life unfolds within a phylogenetic context. Comparative phylogenetic methods are statistical approaches for analyzing historical patterns along phylogenetic trees. This task view describes R packages that implement a variety of different comparative phylogenetic methods. This is an active research area and much of the information is subject to change.<br />
<br />
'''Ancestral state reconstruction''' : Continuous characters can be reconstructed using maximum likelihood, generalised least squares or independent contrasts in <span style="color: green"> ape </span>. Root ancestral character states under Brownian motion or Ornstein-Uhlenbeck models can be reconstructed in <span style="color: green"> OUCH </span>, though ancestral states at the internal nodes are not. Discrete characters can be reconstructed using a variety of Markovian models that parameterize the transition rates among states using <span style="color: green"> ape </span>.<br />
<br />
'''Diversification Analysis''': Lineage through time plots can be done in <span style="color: green"> ape </span>and <span style="color: green"> laser </span>. A simple birth-death model for when you have extant species only (sensu Nee et al. 1994) can be fitted in <span style="color: green"> ape </span> as can survival models and goodness-of-fit tests (as applied to testing of models of diversification). <span style="color: green"> Laser</span> implements likelihood methods using a model testing approach for inferring temporal shifts in diversification rates based on a birth-death or pure-birth process. The gamma statistic (Pybus and Harvey 2000) is also available in <span style="color: green"> laser</span>. Colless and Sackin's topological methods for analyzing diversification are available in <span style="color: green"> apTreeshape </span> as is the test for significant shifts in diversification (sensu Moore, Chan and Donoghue 2004). Net rates of diversification (sensu Magellon and Sanderson) can be calculated in <span style="color: green"> geiger </span>.<br />
<br />
'''Divergence Times''': Non-parametric rate smoothing (NPRS) and penalized likelihood can be implemented in <span style="color: green"> ape </span>.<br />
<br />
'''Phylogenetic Inference''': Maximum likelihood, UPGMA, neighbour joining, bio-nj and fast ME methods of phylogenetic reconstruction are all implemented in the package <span style="color: green"> ape </span>. Phylogenetic trees can be reconstructed using Maximum likelihood, Maximum Parsimony or Hadamard conjugation with <span style="color: green"> phangorn </span>. For more information on importing sequence data, see the Genetics task view.<br />
<br />
'''Time series''': Paleontological time series data can be analyzed using a likelihood-based framework for fitting and comparing models (using a model testing approach) of phyletic evolution (based on the random walk or stasis model) using <span style="color: green"> paleoTS</span>.<br />
<br />
'''Tree Simulations''': Trees can be simulated using a Yule, PDA, biased or speciation specified model in apTreeshape, a birth-death process in <span style="color: green"> geiger </span>, and <span style="color: green"> PhySim </span>. Random trees can be generated in <span style="color: green"> ape </span> by random splitting of edges (for non-parametric trees) or random clustering of tips (for coalescent trees).<br />
<br />
'''Trait evolution''': Independent contrasts for continuous characters can be calculated using ape. Pagel's continuous and discrete analyzes can be calculated in <span style="color: green"> geiger </span>. Ornstein-Uhlenbeck (OU) models can be fitted in <span style="color: green"> geiger</span>, <span style="color: green"> ape</span> and <span style="color: green"> OUCH</span>. In its current implementation, <span style="color: green"> geiger</span> fits only single-optimum models. ANOVA's and MANOVA's in a phylogenetic context can also be implemented in <span style="color: green"> geiger</span>. A GLS linear model (sensu Garland and Ives 2000) can be fitted using <span style="color: green"> PHYLOGR</span>; the more traditional GLS methods (senu Grafen or Martins) can be implemented in <span style="color: green"> ape</span>. Phylogenetic autoregression (sensu Cheverud et al) and Phylogenetic autocorrelation (Moran's I) can be implemented in <span style="color: green"> ape </span> or--if you wish the significance test of Moran's I to be calculated via a randomization procedure--in <span style="color: green"> ade4 </span>.<br />
<br />
'''Trait Simulations''' : Continuous traits can be simulated using brownian motion in <span style="color: green"> OUCH </span> and <span style="color: green"> geiger </span>, the Hansen model in <span style="color: green"> OUCH </span> and a speciational model in <span style="color: green"> geiger </span>. Discrete traits can be simulated using a continuous time Markov model in <span style="color: green"> geiger </span>. Both discrete and continuous traits can be simulated under models where rates change through time in <span style="color: green"> geiger </span>.<br />
<br />
'''Tree Manipulation''' : Branch length scaling using ACDC; Pagel's (1999) lambda, delta and kappa parameters; and the Ornstein-Uhlenbeck alpha parameter (for ultrametric trees only) are available in <span style="color: green"> geiger </span>. Rooting, resolving polytomies, dropping of tips, setting of branch lengths including Grafen's method can all be done using <span style="color: green"> ape </span>. Trees can be pruned from specified nodes using <span style="color: green"> apTreeshape </span> and extinct taxa can be pruned using <span style="color: green"> geiger </span>.<br />
<br />
'''Tree Plotting and Visualization''': User inputted trees can be plotted using <span style="color: green"> ape </span>, <span style="color: green"> ade4 </span> and <span style="color: green"> OUCH </span>. Trees can also be examined (zoomed) and viewed as correlograms using ape. Ancestral state reconstructions can be visualized along branches using <span style="color: green"> ape </span> .<br />
<br />
== R packages as lists ==<br />
<br />
=== Packages on CRAN ===<br />
* [http://cran.r-project.org/web/packages/ade4/index.html ade4]<br />
* [http://cran.r-project.org/web/packages/ape/index.html ape]<br />
* [http://cran.r-project.org/web/packages/apTreeshape/index.html apTreeshape]<br />
* [http://cran.r-project.org/web/packages/geiger/index.html geiger]<br />
* [http://cran.r-project.org/web/packages/laser/index.html laser]<br />
* [http://cran.r-project.org/web/packages/ouch/index.html OUCH]<br />
* [http://cran.r-project.org/web/packages/paleoTS/index.html PaleoTS]<br />
* [http://cran.r-project.org/web/packages/phangorn/index.html phangorn]<br />
* [http://cran.r-project.org/web/packages/PHYLOGR/index.html PHYLOGR]<br />
* [http://cran.r-project.org/web/packages/PhySim/index.html PhySim]<br />
* [http://cran.r-project.org/web/packages/picante/index.html picante]<br />
<br />
=== Packages not yet on CRAN ===<br />
<br />
* [http://r-forge.r-project.org/projects/mattice/ maticce]<br />
* [http://phylobase.r-forge.r-project.org/ phylobase]<br />
* [http://r-forge.r-project.org/projects/rmesquite/ RMesquite]<br />
<br />
=== Development links for packages ===<br />
<br />
* [http://r-forge.r-project.org/projects/ade4/ ade4]<br />
* ape: [http://ape.mpl.ird.fr/ home page] and [https://svn.mpl.ird.fr/ape/ svn repository]<br />
* [http://r-forge.r-project.org/projects/mattice/ maticce]<br />
* [http://r-forge.r-project.org/projects/ouch/ OUCH]<br />
* [http://phylobase.r-forge.r-project.org/ phylobase]<br />
* [http://picante.r-forge.r-project.org/ picante]<br />
* [http://r-forge.r-project.org/projects/rmesquite/ RMesquite]<br />
<br />
==References==<br />
# Butler MA, King AA 2004 Phylogenetic comparative analysis: A modeling approach for adaptive evolution. American Naturalist 164, 683-695.<br />
# Cheverud JM, Dow MM, Leutenegger W 1985 The quantitative assessment of phylogenetic constraints in comparative analyses: Sexual dimorphism in body weight among primates. Evolution 39, 1335-1351.<br />
# Garland T, Harvey PH, Ives AR 1992 Procedures for the analysis of comparative data using phylogenetically independent contrasts. Systematic Biology 41, 18-32.<br />
# Hansen TF 1997. Stabilizing selection and the comparative analysis of adaptation. Evolution 51: 1341-1351.<br />
# Magallon S, Sanderson, M.J. 2001. Absolute Diversification Rates in Angiosperm Clades. Evolution 55(9):1762-1780.<br />
# Moore, BR, Chan, KMA, Donoghue, MJ (2004) Detecting diversification rate variation in supertrees. In Bininda-Emonds ORP (ed) Phylogenetic Supertrees: Combining Information to Reveal the Tree of Life, Kluwer Academic pgs 487-533.<br />
# Nee S, May RM, Harvey PH 1994. The reconstructed evolutionary process. Philosophical Transactions of the Royal Society of London Series B Biological Sciences 344: 305-311.<br />
# Pagel M 1999 Inferring the historical patterns of biological evolution. Nature 401, 877-884<br />
# Pybus OG, Harvey PH 2000. Testing macro-evolutionary models using incomplete molecular phylogenies. Proceedings of the Royal Society of London Series B Biological Sciences 267, 2267-2272.<br />
<br />
[[Category:HowTo]][[Category:R Help]][[Category:Comparative Methods Help]]</div>Hilmarhttps://www.r-phylo.org/w/index.php?title=Available_Packages_and_Analyses&diff=622&oldid=prevHilmar at 02:41, 16 March 20082008-03-16T02:41:37Z<p></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 22:41, 15 March 2008</td>
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<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>#<del style="font-weight: bold; text-decoration: none;">REDIRECT </del>[[<del style="font-weight: bold; text-decoration: none;">Packages&AnalysesAvailable</del>]]</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">==Packages and Analyses available in R==</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">The history of life unfolds within a phylogenetic context. Comparative phylogenetic methods are statistical approaches for analyzing historical patterns along phylogenetic trees. This task view describes R packages that implement a variety of different comparative phylogenetic methods. This is an active research area and much of the information is subject to change.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Ancestral state reconstruction : Continuous characters can be reconstructed using maximum likelihood, generalised least squares or independent contrasts in <span style="color: green"> ape </span>. Root ancestral character states under Brownian motion or Ornstein-Uhlenbeck models can be reconstructed in <span style="color: green"> OUCH </span>, though ancestral states at the internal nodes are not. Discrete characters can be reconstructed using a variety of Markovian models that parameterize the transition rates among states using <span style="color: green"> ape </span>.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Diversification Analysis: Lineage through time plots can be done in <span style="color: green"> ape </span>and <span style="color: green"> laser </span>. A simple birth-death model for when you have extant species only (sensu Nee et al. 1994) can be fitted in <span style="color: green"> ape </span> as can survival models and goodness-of-fit tests (as applied to testing of models of diversification). <span style="color: green"> Laser</span> implements likelihood methods using a model testing approach for inferring temporal shifts in diversification rates based on a birth-death or pure-birth process. The gamma statistic (Pybus and Harvey 2000) is also available in <span style="color: green"> laser</span>. Colless and Sackin's topological methods for analyzing diversification are available in <span style="color: green"> apTreeshape </span> as is the test for significant shifts in diversification (sensu Moore, Chan and Donoghue 2004). Net rates of diversification (sensu Magellon and Sanderson) can be calculated in <span style="color: green"> geiger </span>.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Divergence Times: Non-parametric rate smoothing (NPRS) and penalized likelihood can be implemented in <span style="color: green"> ape </span>.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Phylogenetic Inference: Maximum likelihood, UPGMA, neighbour joining, bio-nj and fast ME methods of phylogenetic reconstruction are all implemented in the package <span style="color: green"> ape </span>. For more information on importing sequence data, see the Genetics task view.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Time series: Paleontological time series data can be analyzed using a likelihood-based framework for fitting and comparing models (using a model testing approach) of phyletic evolution (based on the random walk or stasis model) using <span style="color: green"> paleoTS</span>.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Tree Simulations: Trees can be simulated using a Yule, PDA, biased or speciation specified model in apTreeshape, a birth-death process in <span style="color: green"> geiger </span>, and <span style="color: green"> PhySim </span>. Random trees can be generated in <span style="color: green"> ape </span> by random splitting of edges (for non-parametric trees) or random clustering of tips (for coalescent trees).</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Trait evolution: Independent contrasts for continuous characters can be calculated using ape. Pagel's continuous and discrete analyzes can be calculated in <span style="color: green"> geiger </span>. Ornstein-Uhlenbeck (OU) models can be fitted in <span style="color: green"> geiger</span>, <span style="color: green"> ape</span> and <span style="color: green"> OUCH</span>. In its current implementation, <span style="color: green"> geiger</span> fits only single-optimum models. ANOVA's and MANOVA's in a phylogenetic context can also be implemented in <span style="color: green"> geiger</span>. A GLS linear model (sensu Garland and Ives 2000) can be fitted using <span style="color: green"> PHYLOGR</span>; the more traditional GLS methods (senu Grafen or Martins) can be implemented in <span style="color: green"> ape</span>. Phylogenetic autoregression (sensu Cheverud et al) and Phylogenetic autocorrelation (Moran's I) can be implemented in <span style="color: green"> ape </span> or--if you wish the significance test of Moran's I to be calculated via a randomization procedure--in <span style="color: green"> ade4 </span>.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Trait Simulations : Continuous traits can be simulated using brownian motion in <span style="color: green"> OUCH </span> and <span style="color: green"> geiger </span>, the Hansen model in <span style="color: green"> OUCH </span> and a speciational model in <span style="color: green"> geiger </span>. Discrete traits can be simulated using a continuous time Markov model in <span style="color: green"> geiger </span>. Both discrete and continuous traits can be simulated under models where rates change through time in <span style="color: green"> geiger </span>.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Tree Manipulation : Branch length scaling using ACDC; Pagel's (1999) lambda, delta and kappa parameters; and the Ornstein-Uhlenbeck alpha parameter (for ultrametric trees only) are available in <span style="color: green"> geiger </span>. Rooting, resolving polytomies, dropping of tips, setting of branch lengths including Grafen's method can all be done using <span style="color: green"> ape </span>. Trees can be pruned from specified nodes using <span style="color: green"> apTreeshape </span> and extinct taxa can be pruned using <span style="color: green"> geiger </span>.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Tree Plotting and Visualization: User inputted trees can be plotted using <span style="color: green"> ape </span>, <span style="color: green"> ade4 </span> and <span style="color: green"> OUCH </span>. Trees can also be examined (zoomed) and viewed as correlograms using ape. Ancestral state reconstructions can be visualized along branches using <span style="color: green"> ape </span> .</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">==CRAN packages==</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [http://cran.r-project.org/web/packages/ape/index.html| ade4]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [http://cran.r-project.org/web/packages/ade4/index.html| ape]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [http://cran.r-project.org/web/packages/apTreeshape/index.html| apTreeshape]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [http://cran.r-project.org/web/packages/geiger/index.html| geiger]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [http://cran.r-project.org/web/packages/laser/index.html| laser]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [http://cran.r-project.org/web/packages/ouch/index.html| OUCH]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [http://cran.r-project.org/web/packages/paleoTS/index.html| PaleoTS]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [http://cran.r-project.org/web/packages/PHYLOGR/index.html| PHYLOGR]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [http://cran.r-project.org/web/packages/PhySim/index.html| PhySim]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">==References==</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># <ins style="font-weight: bold; text-decoration: none;">Butler MA, King AA 2004 Phylogenetic comparative analysis: A modeling approach for adaptive evolution. American Naturalist 164, 683-695.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Cheverud JM, Dow MM, Leutenegger W 1985 The quantitative assessment of phylogenetic constraints in comparative analyses: Sexual dimorphism in body weight among primates. Evolution 39, 1335-1351.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Garland T, Harvey PH, Ives AR 1992 Procedures for the analysis of comparative data using phylogenetically independent contrasts. Systematic Biology 41, 18-32.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Hansen TF 1997. Stabilizing selection and the comparative analysis of adaptation. Evolution 51: 1341-1351.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Magallon S, Sanderson, M.J. 2001. Absolute Diversification Rates in Angiosperm Clades. Evolution 55(9):1762-1780.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Moore, BR, Chan, KMA, Donoghue, MJ (2004) Detecting diversification rate variation in supertrees. In Bininda-Emonds ORP (ed) Phylogenetic Supertrees: Combining Information to Reveal the Tree of Life, Kluwer Academic pgs 487-533.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Nee S, May RM, Harvey PH 1994. The reconstructed evolutionary process. Philosophical Transactions of the Royal Society of London Series B Biological Sciences 344: 305-311.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Pagel M 1999 Inferring the historical patterns of biological evolution. Nature 401, 877-884</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Pybus OG, Harvey PH 2000. Testing macro-evolutionary models using incomplete molecular phylogenies. Proceedings of the Royal Society of London Series B Biological Sciences 267, 2267-2272.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[[<ins style="font-weight: bold; text-decoration: none;">Category:HowTo]][[Category:R Help]][[Category:Comparative Methods Help</ins>]]</div></td></tr>
</table>Hilmarhttps://www.r-phylo.org/w/index.php?title=Available_Packages_and_Analyses&diff=621&oldid=prevHilmar: HowTo/Taskview moved to Available Packages and Analyses2008-03-16T02:39:45Z<p><a href="/wiki/HowTo/Taskview" class="mw-redirect" title="HowTo/Taskview">HowTo/Taskview</a> moved to <a href="/wiki/Available_Packages_and_Analyses" title="Available Packages and Analyses">Available Packages and Analyses</a></p>
<p><b>New page</b></p><div>#REDIRECT [[Packages&AnalysesAvailable]]</div>Hilmar