---
name: "ChromHMM"
section: "1"
platform: "linux"
package: "chromhmm"
version: "1.26+dfsg-3"
release: "Debian 13 (Trixie)"
platforms: ["linux"]
url: "https://new.carta.tech/ChromHMM"
---

# ChromHMM(1)

Learning and analysis chromatin states using a multivariate Hidden Markov Model

## 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.**