HMMSeg is a program for the scale-specific segmention of continuous
genomic data using hidden Markov models (HMMs). It can segment
multiple datasets simultaneously. Scale-specificity is achieved via
an optional smoothing step using wavelets. HMMSeg is written in Java
and may be downloaded for unrestricted use below. It has been tested
on Windows and several Unix-type operating systems.
HMMSeg was written by Nathan Day and Andrew Hemmaplardh at the
University of Washington.
Version release information may be found
Installation instructions. Since HMMSeg is distributed as
a JAR archive, no installation should be necessary. Run as
-jar <path>HMMSeg.jar [options] [filelists]. The program
requires Java 1.5 or newer to run. See the help file for more information.
Manuscript. See the article, "Unsupervised
segmentation of continuous genomic data," Bioinformatics 2007
Essentials of wavelets (pdf)
A short description of the wavelet analysis implemented in HMMSeg.
Example An example
HMMSeg analysis with step-by-step instructions.
Validation and testing analysis