The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
Analysis with profile hidden Markov models
aphid
is an R package for the development and
application of hidden Markov models and profile HMMs for biological
sequence analysis. Functions are included for multiple and pairwise
sequence alignment, model construction and parameter optimization,
calculation of conditional probabilities (using the forward, backward
and Viterbi algorithms), tree-based sequence weighting, sequence
simulation, and file import/export compatible with the HMMER software package.
aphid
also includes functions for developing and working
with standard hidden Markov models.
This package was written based on the algorithms described in the book Biological Sequence Analysis by Richard Durbin, Sean Eddy, Anders Krogh and Graeme Mitchison. This book offers an in depth explanation of hidden Markov models and profile HMMs for users of all levels of familiarity. Many of the examples and datasets in the package are directly derived from the text, which serves as a useful primer for this package.
To download aphid
from CRAN and load the package,
run
install.packages("aphid")
library("aphid")
To download the development version from GitHub, first ensure a C/C++ compliler is available and the devtools R package is installed. Linux users will generally have a compiler installed by default; however Windows users may need to download Rtools and Mac OSX users will need Xcode (note that these are not R packages). Install and load the package by running
::install_github("shaunpwilkinson/aphid", build_vignettes = TRUE)
devtoolslibrary("aphid")
An overview of the package and its functions can be found by running
?aphid
To view the tutorial, run
vignette("aphid-vignette")
If you experience a problem using this package please feel free to raise it as an issue on GitHub.
This software was developed at Victoria University of Wellington with funding from a Rutherford Foundation Postdoctoral Research Fellowship award from the Royal Society of New Zealand.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.