NAME
ChromHMM - Learning and analysis chromatin states using a multivariate Hidden Markov Model
SYNOPSIS
java -Xmx[GB]g -jar /usr/share/java/chromhmm.jar [options]
DESCRIPTION
ChromHMM is software for learning and characterizing chromatin states. ChromHMM can integrate multiple chromatin datasets such as ChIP-seq data of various histone modifications to discover de novo the major re-occuring combinatorial and spatial patterns of marks. ChromHMM is based on a multivariate Hidden Markov Model that explicitly models the presence or absence of each chromatin mark. The resulting model can then be used to systematically annotate a genome in one or more cell types. By automatically computing state enrichments for large-scale functional and annotation datasets ChromHMM facilitates the biological characterization of each state. ChromHMM also produces files with genome-wide maps of chromatin state annotations that can be directly visualized in a genome browser.
OPTIONS
- LearnModel
-
Takes a set of binarized data files, learns chromatin state models, and by default produces a segmentation, generates browser output with default settings, and calls OverlapEnrichment and NeighborhoodEnrichments with default settings for the specified genome assembly. A webpage is a created with links to all the files and images created.
- BinarizeBed
-
Converts a set of bed files of aligned reads into binarized data files for model learning and optionally prints the intermediate signal files.
- BinarizeBam
-
Converts a set of bam files of aligned reads into binarized data files for model learning and optionally prints the intermediate signal files.
- BinarizeSignal
-
Converts a set of signal files into binarized files.
- MakeSegmentation
-
Takes a learned model and binarized data and outputs a segmentation.
- MakeBrowserFiles
-
Can convert segmentation files into a browser viewable format.
- OverlapEnrichment
-
Shows the enrichment of each state of a segmentation for a set of external data.
- NeighborhoodEnrichment
-
Shows the enrichment of each state relative to a set of anchor positions.
- CompareModels
-
Can compare models with different numbers of states in terms of correlation in emission parameters.
- Reorder
-
Allows reordering the states of the model, the columns of the emission matrix, or adding state labels.
- EvalSubset
-
Can be used to evaluate the extent to which a subset of marks can recover a segmentation using the full set of marks.
- StatePruning
-
Can be used to prune states from a model in order to initialize models when using the non-default two pass approach.
SEE ALSO
http://compbio.mit.edu/ChromHMM/
AUTHOR
ChromHMM was written by Jason Ernst.