doi: 10.1093/bioinformatics/btm096.
Epub 2007 Mar 23.
Unsupervised segmentation of continuous genomic data
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- PMID: 17384021
- DOI: 10.1093/bioinformatics/btm096
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Unsupervised segmentation of continuous genomic data
Bioinformatics.
.
Abstract
The advent of high-density, high-volume genomic data has created the need for tools to summarize large datasets at multiple scales. HMMSeg is a command-line utility for the scale-specific segmentation of continuous genomic data using hidden Markov models (HMMs). Scale specificity is achieved by an optional wavelet-based smoothing operation. HMMSeg is capable of handling multiple datasets simultaneously, rendering it ideal for integrative analysis of expression, phylogenetic and functional genomic data.
Availability: http://noble.gs.washington.edu/proj/hmmseg
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