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Armatus specifications


Unique identifier OMICS_14191
Name Armatus
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data A matrice file
Input format TXT
Operating system Unix/Linux
License BSD 3-clause “New” or “Revised” License
Computer skills Advanced
Version 2.2
Stability Stable
C++, Boost
Maintained Yes




No version available


  • person_outline Carl Kingsford

Publication for Armatus

Armatus citations


Computational Methods for Assessing Chromatin Hierarchy

Comput Struct Biotechnol J
PMCID: 5910504
PMID: 29686798
DOI: 10.1016/j.csbj.2018.02.003

[…] For example, TADtool (as a Python package) enables the direct export of TADs called using a set of parameters for both directionality and insulation indices []. Other TAD callers, such as TADbit [], Armatus [], and TADtree [], exhibit balanced performance for most parameters for experimental and simulated data. Interaction callers, such as HOMER [] and HiCCUPS, [,] yield the highest proportion of […]


Stratification of TAD boundaries reveals preferential insulation of super enhancers by strong boundaries

Nat Commun
PMCID: 5803259
PMID: 29416042
DOI: 10.1038/s41467-018-03017-1

[…] ssociating domains (TADs)– and sub-TADs, as well as gene neighborhoods. Several algorithms have been developed to reveal this hierarchical chromatin organization, including Directionality Index (DI), Armatus, TADtree, insulation index (Crane), IC-finder, and others. However, none of these studies has systematically explored the properties of TAD boundaries. Although TADs are seemingly invariant ac […]


Sequence based multiscale modeling for high throughput chromosome conformation capture (Hi C) data analysis

PLoS One
PMCID: 5800693
PMID: 29408904
DOI: 10.1371/journal.pone.0191899

[…] d can be efficiently evaluated by using dynamic programming. Meanwhile, a resolution parameter is considered to identify TADs at various scales. This algorithm has been incorporated into the software Armatus []. Further, a block-wise segmentation model called HiCseg [] is proposed. This method reduces the problem of maximizing the likelihood with respect to the block boundaries into a 1D segmentat […]


Sub kb Hi C in D. melanogaster reveals conserved characteristics of TADs between insect and mammalian cells

Nat Commun
PMCID: 5768742
PMID: 29335463
DOI: 10.1038/s41467-017-02526-9
call_split See protocol

[…] genome using bowtie2 (v2.2.9) (Supplementary Methods). After filtering, the valid contact matrix was normalized using ICE as described. After normalization, domains were annotated using the software Armatus with the scaling parameter, gamma, set to 0.9. The other parameters in Armatus for Drosophila data were: -R –N –g 2.0 –m –r 1 –s 0.1 (where here –r 1 refers to single fragment resolution). For […]


SMARCB1 is required for widespread BAF complex mediated activation of enhancers and bivalent promoters

Nat Genet
PMCID: 5803080
PMID: 28945250
DOI: 10.1038/ng.3958
call_split See protocol

[…] nteraction matrix of each chromosome was generated for Hi-C data. The interaction matrix was normalized by KR normalization. The normalized interaction matrix was used as input for identifying TAD by Armatus. […]


Activation of the alpha globin gene expression correlates with dramatic upregulation of nearby non globin genes and changes in local and large scale chromatin spatial structure

PMCID: 5504709
PMID: 28693562
DOI: 10.1186/s13072-017-0142-4

[…] , which provides a set of dynamic programming algorithms to assess an ensemble of TAD segmentations derived from a TAD scoring function. We used its optimal segmentation finder, which is based on the Armatus algorithm [] using the TAD scoring function from that study. The algorithm finds the global TAD segmentation of a contact map having the highest aggregate score.Chromatin compartments were ide […]


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Armatus institution(s)
Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA; Joint Carnegie Mellon University — University of Pittsburgh PhD Program in Computational Biology, Pittsburgh, PA, USA
Armatus funding source(s)
This work has been partially funded by National Science Foundation (CCF-1256087, CCF-1053918, and EF-0849899) and National Institutes of Health (R21AI085376, R01HG007104).

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