gphmm: Generalized Pair Hidden Markov Chain Model for Sequence Alignment

Implementation of a generalized pair hidden Markov chain model (GPHMM) that can be used to compute the probability of alignment between two sequences of nucleotides (e.g., a reference sequence and a noisy sequenced read). The model can be trained on a dataset where the noisy sequenced reads are known to have been sequenced from known reference sequences. If no training sets are available default parameters can be used.

Version: 0.99.0
Imports: Rcpp, parallel, dplyr, Biostrings, stringr, stringi, stats, docopt
LinkingTo: Rcpp
Suggests: testthat, knitr, jsonlite
Published: 2017-10-02
Author: Fanny Perraudeau [aut, cre], James Bullard [aut]
Maintainer: Fanny Perraudeau <perraudeau.f at gmail.com>
License: Artistic-2.0
NeedsCompilation: yes
Materials: README
CRAN checks: gphmm results

Downloads:

Reference manual: gphmm.pdf
Vignettes: gphmm
Package source: gphmm_0.99.0.tar.gz
Windows binaries: r-prerel: gphmm_0.99.0.zip, r-release: gphmm_0.99.0.zip, r-oldrel: gphmm_0.99.0.zip
OS X binaries: r-prerel: gphmm_0.99.0.tgz, r-release: gphmm_0.99.0.tgz

Linking:

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