tag:crantastic.org,2005:/authors/6561Latest activity for Venelin Mitov2019-12-05T11:03:08Zcrantastic.orgtag:crantastic.org,2005:TimelineEvent/956082019-12-05T11:03:08Z2019-12-05T11:03:08ZPOUMM was upgraded to version 2.1.6<a href="/packages/POUMM">POUMM</a> was <span class="action">upgraded</span> to version <a href="/packages/POUMM/versions/90867">2.1.6</a><br /><h3>Package description:</h3><p>The Phylogenetic Ornstein-Uhlenbeck Mixed Model (POUMM) allows to estimate the phylogenetic heritability of continuous traits, to test hypotheses of neutral evolution versus stabilizing selection, to quantify the strength of stabilizing selection, to estimate measurement error and to make predictions about the evolution of a phenotype and phenotypic variation in a population. The package implements combined maximum likelihood and Bayesian inference of the univariate Phylogenetic Ornstein-Uhlenbeck Mixed Model, fast parallel likelihood calculation, maximum likelihood inference of the genotypic values at the tips, functions for summarizing and plotting traces and posterior samples, functions for simulation of a univariate continuous trait evolution model along a phylogenetic tree. So far, the package has been used for estimating the heritability of quantitative traits in macroevolutionary and epidemiological studies, see e.g. Bertels et al. (2017) <doi:10.1093/molbev/msx246> and Mitov and Stadler (2018) <doi:10.1093/molbev/msx328>. The algorithm for parallel POUMM likelihood calculation has been published in Mitov and Stadler (2019) <doi:10.1111/2041-210X.13136>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/950462019-11-21T16:23:28Z2019-11-21T16:23:28ZPCMBaseCpp was upgraded to version 0.1.7<a href="/packages/PCMBaseCpp">PCMBaseCpp</a> was <span class="action">upgraded</span> to version <a href="/packages/PCMBaseCpp/versions/90336">0.1.7</a><br /><h3>Package description:</h3><p>Provides a C++ backend for multivariate phylogenetic comparative models implemented in the R-package 'PCMBase'. Can be used in combination with 'PCMBase' to enable fast and parallel likelihood calculation. Implements the pruning likelihood calculation algorithm described in Mitov et al. (2018) <arXiv:1809.09014>. Uses the 'SPLITT' C++ library for parallel tree traversal described in Mitov and Stadler (2018) <doi:10.1111/2041-210X.13136>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/946312019-11-11T13:42:57Z2019-11-11T13:42:57ZPCMBaseCpp was upgraded to version 0.1.6<a href="/packages/PCMBaseCpp">PCMBaseCpp</a> was <span class="action">upgraded</span> to version <a href="/packages/PCMBaseCpp/versions/89976">0.1.6</a><br /><h3>Package description:</h3><p>Provides a C++ backend for multivariate phylogenetic comparative models implemented in the R-package 'PCMBase'. Can be used in combination with 'PCMBase' to enable fast and parallel likelihood calculation. Implements the pruning likelihood calculation algorithm described in Mitov et al. (2018) <arXiv:1809.09014>. Uses the 'SPLITT' C++ library for parallel tree traversal described in Mitov and Stadler (2018) <doi:10.1111/2041-210X.13136>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/934142019-10-06T12:41:59Z2019-10-06T12:41:59ZPCMBaseCpp was released<a href="/packages/PCMBaseCpp">PCMBaseCpp</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>Provides a C++ backend for multivariate phylogenetic comparative models implemented in the R-package 'PCMBase'. Can be used in combination with 'PCMBase' to enable fast and parallel likelihood calculation. Implements the pruning likelihood calculation algorithm described in Mitov et al. (2018) <arXiv:1809.09014>. Uses the 'SPLITT' C++ library for parallel tree traversal described in Mitov and Stadler (2018) <doi:10.1111/2041-210X.13136>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/925892019-09-11T16:42:39Z2019-09-11T16:42:39ZPCMBase was upgraded to version 1.2.10<a href="/packages/PCMBase">PCMBase</a> was <span class="action">upgraded</span> to version <a href="/packages/PCMBase/versions/88047">1.2.10</a><br /><h3>Package description:</h3><p>Phylogenetic comparative methods represent models of continuous trait data associated with the tips of a phylogenetic tree. Examples of such models are Gaussian continuous time branching stochastic processes such as Brownian motion (BM) and Ornstein-Uhlenbeck (OU) processes, which regard the data at the tips of the tree as an observed (final) state of a Markov process starting from an initial state at the root and evolving along the branches of the tree. The PCMBase R package provides a general framework for manipulating such models. This framework consists of an application programming interface for specifying data and model parameters, and efficient algorithms for simulating trait evolution under a model and calculating the likelihood of model parameters for an assumed model and trait data. The package implements a growing collection of models, which currently includes BM, OU, BM/OU with jumps, two-speed OU as well as mixed Gaussian models, in which different types of the above models can be associated with different branches of the tree. The PCMBase package is limited to trait-simulation and likelihood calculation of (mixed) Gaussian phylogenetic models. The PCMFit package provides functionality for ML and Bayesian fit of these models to tree and trait data. The package web-site <https://venelin.github.io/PCMBase/> provides access to the documentation and other resources.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/865952019-03-27T12:42:24Z2019-03-27T12:42:24ZPOUMM was upgraded to version 2.1.5<a href="/packages/POUMM">POUMM</a> was <span class="action">upgraded</span> to version <a href="/packages/POUMM/versions/82321">2.1.5</a><br /><h3>Package description:</h3><p>The Phylogenetic Ornstein-Uhlenbeck Mixed Model (POUMM) allows to estimate the phylogenetic heritability of continuous traits, to test hypotheses of neutral evolution versus stabilizing selection, to quantify the strength of stabilizing selection, to estimate measurement error and to make predictions about the evolution of a phenotype and phenotypic variation in a population. The package implements combined maximum likelihood and Bayesian inference of the univariate Phylogenetic Ornstein-Uhlenbeck Mixed Model, fast parallel likelihood calculation, maximum likelihood inference of the genotypic values at the tips, functions for summarizing and plotting traces and posterior samples, functions for simulation of a univariate continuous trait evolution model along a phylogenetic tree. So far, the package has been used for estimating the heritability of quantitative traits in macroevolutionary and epidemiological studies, see e.g. Bertels et al. (2017) <doi:10.1093/molbev/msx246> and Mitov and Stadler (2018) <doi:10.1093/molbev/msx328>. The algorithm for parallel POUMM likelihood calculation has been published in Mitov and Stadler (2019) <doi:10.1111/2041-210X.13136>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/860212019-03-15T11:02:17Z2019-03-15T11:02:17ZPCMBase was upgraded to version 1.2.9<a href="/packages/PCMBase">PCMBase</a> was <span class="action">upgraded</span> to version <a href="/packages/PCMBase/versions/81803">1.2.9</a><br /><h3>Package description:</h3><p>Phylogenetic comparative methods represent models of continuous trait data associated with the tips of a phylogenetic tree. Examples of such models are Gaussian continuous time branching stochastic processes such as Brownian motion (BM) and Ornstein-Uhlenbeck (OU) processes, which regard the data at the tips of the tree as an observed (final) state of a Markov process starting from an initial state at the root and evolving along the branches of the tree. The PCMBase R package provides a general framework for manipulating such models. This framework consists of an application programming interface for specifying data and model parameters, and efficient algorithms for simulating trait evolution under a model and calculating the likelihood of model parameters for an assumed model and trait data. The package implements a growing collection of models, which currently includes BM, OU, BM/OU with jumps, two-speed OU as well as mixed Gaussian models, in which different types of the above models can be associated with different branches of the tree. The PCMBase package is limited to trait-simulation and likelihood calculation of (mixed) Gaussian phylogenetic models. The PCMFit package provides functionality for ML and Bayesian fit of these models to tree and trait data. The package web-site <https://venelin.github.io/PCMBase/> provides access to the documentation and other resources.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/822622018-12-01T00:02:15Z2018-12-01T00:02:15ZPCMBase was released<a href="/packages/PCMBase">PCMBase</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>Phylogenetic comparative methods represent models of continuous trait data associated with the tips of a phylogenetic tree. Examples of such models are Gaussian continuous time branching stochastic processes such as Brownian motion (BM) and Ornstein-Uhlenbeck (OU) processes, which regard the data at the tips of the tree as an observed (final) state of a Markov process starting from an initial state at the root and evolving along the branches of the tree. The PCMBase R package provides a general framework for manipulating such models. This framework consists of an application programming interface for specifying data and model parameters, and efficient algorithms for simulating trait evolution under a model and calculating the likelihood of model parameters for an assumed model and trait data. The package implements a growing collection of models, which currently includes BM, OU, BM/OU with jumps, two-speed OU as well as mixed Gaussian models, in which different types of the above models can be associated with different branches of the tree. The PCMBase package is limited to trait-simulation and likelihood calculation of (mixed) Gaussian phylogenetic models. The PCMFit package provides functionality for ML and Bayesian fit of these models to tree and trait data. The package web-site <https://venelin.github.io/PCMBase/> provides access to the documentation and other resources.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/817712018-11-15T17:42:29Z2018-11-15T17:42:29ZPOUMM was upgraded to version 2.1.2<a href="/packages/POUMM">POUMM</a> was <span class="action">upgraded</span> to version <a href="/packages/POUMM/versions/77801">2.1.2</a><br /><h3>Package description:</h3><p>The Phylogenetic Ornstein-Uhlenbeck Mixed Model (POUMM) allows to estimate the phylogenetic heritability of continuous traits, to test hypotheses of neutral evolution versus stabilizing selection, to quantify the strength of stabilizing selection, to estimate measurement error and to make predictions about the evolution of a phenotype and phenotypic variation in a population. The package implements combined maximum likelihood and Bayesian inference of the univariate Phylogenetic Ornstein-Uhlenbeck Mixed Model, fast parallel likelihood calculation, maximum likelihood inference of the genotypic values at the tips, functions for summarizing and plotting traces and posterior samples, functions for simulation of a univariate continuous trait evolution along a phylogenetic tree. For examples on using the package, see the package vignettes.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/641012017-07-02T14:41:42Z2017-07-02T14:41:42ZPOUMM was upgraded to version 1.3.2<a href="/packages/POUMM">POUMM</a> was <span class="action">upgraded</span> to version <a href="/packages/POUMM/versions/61324">1.3.2</a><br /><h3>Package description:</h3><p>The Phylogenetic Ornstein-Uhlenbeck Mixed Model (POUMM) allows to estimate the phylogenetic heritability of continuous traits, to test hypotheses of neutral evolution versus stabilizing selection, to quantify the strength of stabilizing selection, to estimate measurement error and to make predictions about the evolution of a phenotype and phenotypic variation in a population. The package implements combined maximum likelihood and Bayesian inference of the univariate Phylogenetic Ornstein-Uhlenbeck Mixed Model, fast parallel likelihood calculation, maximum likelihood inference of the genotypic values at the tips, functions for summarizing and plotting traces and posterior samples, functions for simulation of a univariate continuous trait evolution along a phylogenetic tree. A quick example on using the POUMM package can be found in the README. More elaborate examples and use-cases are provided in the vignette "A User Guide to The POUMM R-package".</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/635732017-06-15T23:21:40Z2017-06-15T23:21:40ZPOUMM was upgraded to version 1.3.0<a href="/packages/POUMM">POUMM</a> was <span class="action">upgraded</span> to version <a href="/packages/POUMM/versions/60805">1.3.0</a><br /><h3>Package description:</h3><p>The Phylogenetic Ornstein-Uhlenbeck Mixed Model (POUMM) allows to estimate the phylogenetic heritability of continuous traits, to test hypotheses of neutral evolution versus stabilizing selection, to quantify the strength of stabilizing selection, to estimate measurement error and to make predictions about the evolution of a phenotype and phenotypic variation in a population. The package implements combined maximum likelihood and Bayesian inference of the univariate Phylogenetic Ornstein-Uhlenbeck Mixed Model, fast parallel likelihood calculation, maximum likelihood inference of the genotypic values at the tips, functions for summarizing and plotting traces and posterior samples, functions for simulation of a univariate continuous trait evolution along a phylogenetic tree. A quick example on using the POUMM package can be found in the README. More elaborate examples and use-cases are provided in the vignette "A User Guide to The POUMM R-package".</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/607862017-03-27T14:01:35Z2017-03-27T14:01:35ZPOUMM was upgraded to version 1.2.2<a href="/packages/POUMM">POUMM</a> was <span class="action">upgraded</span> to version <a href="/packages/POUMM/versions/58177">1.2.2</a><br /><h3>Package description:</h3><p>The Phylogenetic Ornstein-Uhlenbeck Mixed Model (POUMM) allows to estimate the phylogenetic heritability of continuous traits, to test hypotheses of neutral evolution versus stabilizing selection, to quantify the strength of stabilizing selection, to estimate measurement error and to make predictions about the evolution of a phenotype and phenotypic variation in a population. The package implements combined maximum likelihood and Bayesian inference of the univariate Phylogenetic Ornstein-Uhlenbeck Mixed Model, fast POUMM likelihood calculation, maximum likelihood inference of the genotypic values at the tips, functions for summarizing and plotting traces and posterior samples, functions for simulation of a univariate continuous trait evolution along a phylogenetic tree. A quick example on using the POUMM package can be found in the README. More elaborate examples and use-cases are provided in the vignette "A User Guide to The POUMM R-package".</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/600662017-03-13T18:10:50Z2017-03-13T18:10:50ZPOUMM was released<a href="/packages/POUMM">POUMM</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>The Phylogenetic Ornstein-Uhlenbeck Mixed Model (POUMM) allows to estimate the phylogenetic heritability of continuous traits, to test hypotheses of neutral evolution versus stabilizing selection, to quantify the strength of stabilizing selection, to estimate measurement error and to make predictions about the evolution of a phenotype and phenotypic variation in a population. The package implements combined maximum likelihood and Bayesian inference of the univariate Phylogenetic Ornstein-Uhlenbeck Mixed Model, fast parallel likelihood calculation, maximum likelihood inference of the genotypic values at the tips, functions for summarizing and plotting traces and posterior samples, functions for simulation of a univariate continuous trait evolution model along a phylogenetic tree. So far, the package has been used for estimating the heritability of quantitative traits in macroevolutionary and epidemiological studies, see e.g. Bertels et al. (2017) <doi:10.1093/molbev/msx246> and Mitov and Stadler (2018) <doi:10.1093/molbev/msx328>. The algorithm for parallel POUMM likelihood calculation has been published in Mitov and Stadler (2019) <doi:10.1111/2041-210X.13136>.</p>crantastic.org