CRAN/E | AnaCoDa

AnaCoDa

Analysis of Codon Data under Stationarity using a Bayesian Framework

Installation

About

Is a collection of models to analyze genome scale codon data using a Bayesian framework. Provides visualization routines and checkpointing for model fittings. Currently published models to analyze gene data for selection on codon usage based on Ribosome Overhead Cost (ROC) are: ROC (Gilchrist et al. (2015) doi:10.1093/gbe/evv087), and ROC with phi (Wallace & Drummond (2013) doi:10.1093/molbev/mst051). In addition 'AnaCoDa' contains three currently unpublished models. The FONSE (First order approximation On NonSense Error) model analyzes gene data for selection on codon usage against of nonsense error rates. The PA (PAusing time) and PANSE (PAusing time + NonSense Error) models use ribosome footprinting data to analyze estimate ribosome pausing times with and without nonsense error rate from ribosome footprinting data.

github.com/clandere/AnaCoDa

Key Metrics

Version 0.1.4.4
R ≥ 3.3.0
Published 2020-09-15 1291 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks AnaCoDa results

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Maintainer

Maintainer

Cedric Landerer

cedric.landerer@gmail.com

Authors

Authors@R

Material

Reference manual
Package source

In Views

Bayesian

Vignettes

Analyzing Codon Data

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

AnaCoDa archive

Depends

R ≥ 3.3.0
Rcpp ≥ 0.11.3
VGAM
methods
mvtnorm

Suggests

knitr
Hmisc
coda
testthat
lmodel2
markdown

LinkingTo

Rcpp