aphylo: Statistical Inference and Prediction of Annotations in
Phylogenetic Trees
Implements a parsimonious evolutionary model to analyze and
predict gene-functional annotations in phylogenetic trees as described in Vega
Yon et al. (2021) <doi:10.1371/journal.pcbi.1007948>. With a focus on
computational efficiency, 'aphylo' makes it possible to estimate pooled
phylogenetic models, including thousands (hundreds) of annotations (trees) in
the same run. The package also provides the tools for visualization of
annotated phylogenies, calculation of posterior probabilities (prediction,)
and goodness-of-fit assessment featured in Vega Yon et al. (2021).
Version: |
0.2-1 |
Depends: |
R (≥ 3.5.0), ape (≥ 5.0) |
Imports: |
Rcpp (≥ 0.12.1), Matrix, methods, coda, fmcmc, utils, MASS, xml2 |
LinkingTo: |
Rcpp |
Suggests: |
covr, knitr, tinytest, AUC, rmarkdown |
Published: |
2022-01-21 |
Author: |
George Vega Yon
[aut, cre],
National Cancer Institute (NCI) [fnd] (Grant Number 5P01CA196569-02),
USC Biostatistics [cph] |
Maintainer: |
George Vega Yon <g.vegayon at gmail.com> |
BugReports: |
https://github.com/USCbiostats/aphylo/issues |
License: |
MIT + file LICENSE |
URL: |
https://github.com/USCbiostats/aphylo |
NeedsCompilation: |
yes |
Classification/MSC: |
90C35, 90B18, 91D30 |
Citation: |
aphylo citation info |
Materials: |
NEWS ChangeLog |
CRAN checks: |
aphylo results |
Documentation:
Downloads:
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