tileHMM: Hidden Markov Models for ChIP-on-Chip Analysis

This package provides methods and classes to build HMMs that are suitable for the analysis of ChIP-on-chip data. The provided parameter estimation methods include the Baum-Welch algorithm and Viterbi training as well as a combination of both.

Version: 1.0-6
Depends: R (≥ 2.14.2), methods
Suggests: st, preprocessCore
Published: 2013-12-12
Author: Peter Humburg
Maintainer: Peter Humburg <Peter.Humburg at well.ox.ac.uk>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: tileHMM citation info
CRAN checks: tileHMM results


Reference manual: tileHMM.pdf
Vignettes: Using tileHMM for ChIP-on-Chip Analysis
Package source: tileHMM_1.0-6.tar.gz
Windows binaries: r-devel: tileHMM_1.0-6.zip, r-release: tileHMM_1.0-6.zip, r-oldrel: tileHMM_1.0-6.zip
OS X Snow Leopard binaries: r-release: tileHMM_1.0-6.tgz, r-oldrel: tileHMM_1.0-6.tgz
OS X Mavericks binaries: r-release: tileHMM_1.0-6.tgz
Old sources: tileHMM archive