{ "_id": "6a549601ff0138dec5d656ad", "Package": "aphylo", "Title": "Statistical Inference and Prediction of Annotations in\nPhylogenetic Trees", "Authors@R": "c(person(\"George\", \"Vega Yon\", role=c(\"aut\",\"cre\"),\nemail=\"g.vegayon@gmail.com\", comment = c(ORCID = \"0000-0002-3171-0844\")),\nperson(\"National\nCancer Institute (NCI)\", role = \"fnd\", comment = \"Grant Number\n5P01CA196569-02\"),\nperson(\"USC Biostatistics\", role = \"cph\")\n)", "Version": "0.3-6", "Description": "Implements a parsimonious evolutionary model to analyze\nand predict gene-functional annotations in phylogenetic trees\nas described in Vega Yon et al. (2021)\n. Focusing on computational\nefficiency, 'aphylo' makes it possible to estimate pooled\nphylogenetic models, including thousands (hundreds) of\nannotations (trees) in the same run. The package also provides\nthe tools for visualization of annotated phylogenies,\ncalculation of posterior probabilities (prediction) and\ngoodness-of-fit assessment featured in Vega Yon et al. 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Vega Yon ", "committer": "GitHub ", "message": "Accepted on CRAN (fixes documentation) (#29)\n\n", "time": 1768388264 }, "_maintainer": { "name": "George Vega Yon", "email": "g.vegayon@gmail.com", "login": "gvegayon", "bluesky": "@gvegayon.bsky.social", "linkedin": "in/georgevegayon", "description": "Scientist at @UofUEpiBio modeling complex systems using statistical computing. 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"aphylo_mle", "title": "Model estimation using Maximum Likelihood Estimation", "concept": [ "parameter estimation" ], "topics": [ "aphylo_mle", "MLE" ] }, { "page": "aphylo-class", "title": "Annotated Phylogenetic Tree", "concept": [ "Data management functions", "aphylo methods" ], "topics": [ "aphylo", "aphylo-class", "new_aphylo", "new_aphylo.phylo" ] }, { "page": "aphylo-index", "title": "Indexing aphylo objects", "topics": [ "aphylo-index", "[.aphylo", "[<-.aphylo" ] }, { "page": "aphylo-info", "title": "Information about 'aphylo' and 'multiAphylo' objects", "concept": [ "information" ], "topics": [ "aphylo-info", "Nann", "Nannotated", "Ntrees" ] }, { "page": "aphylo-methods", "title": "Plot and print methods for 'aphylo' objects", "concept": [ "aphylo methods" ], "topics": [ "aphylo-methods", "plot.aphylo" ] }, { "page": "aphylo-model", "title": "Formulas in 'aphylo'", "topics": [ "aphylo-formula", "aphylo-model", "aphylo_formula", "eta", "mu_d", "mu_s", "Pi", "psi" ] }, { "page": 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