cubfits: Codon Usage Bias Fits

Estimating mutation and selection coefficients on synonymous codon bias usage based on models of ribosome overhead cost (ROC). Multinomial logistic regression and Markov Chain Monte Carlo are used to estimate and predict protein production rates with/without the presence of expressions and measurement errors. Work flows with examples for simulation, estimation and prediction processes are also provided with parallelization speedup. The whole framework is tested with yeast genome and gene expression data of Yassour (2009).

Version: 0.1-0
Depends: R (≥ 3.0.0), methods
Suggests: seqinr, VGAM, EMCluster
Enhances: pbdMPI (≥ 0.2-2), parallel
Published: 2014-05-19
Author: Wei-Chen Chen [aut, cre], Russell Zaretzki [aut], William Howell [aut], Drew Schmidt [aut], Michael Gilchrist [aut], Students REU13 [ctb]
Maintainer: Wei-Chen Chen <wccsnow at gmail.com>
License: Mozilla Public License 2.0
URL: https://github.com/snoweye/cubfits
NeedsCompilation: yes
Citation: cubfits citation info
Materials: README ChangeLogINSTALL
CRAN checks: cubfits results

Downloads:

Reference manual: cubfits.pdf
Vignettes: cubfits-guide
Package source: cubfits_0.1-0.tar.gz
Windows binaries: r-devel: cubfits_0.1-0.zip, r-release: cubfits_0.1-0.zip, r-oldrel: cubfits_0.1-0.zip
OS X Snow Leopard binaries: r-release: cubfits_0.1-0.tgz, r-oldrel: cubfits_0.1-0.tgz
OS X Mavericks binaries: r-release: cubfits_0.1-0.tgz