Source: chromhmm Maintainer: Debian Med Packaging Team Uploaders: Dylan Aïssi Section: science Priority: optional Build-Depends: debhelper-compat (= 13), javahelper, libhtsjdk-java, libbatik-java, libjheatchart-java Build-Depends-Indep: default-jdk Standards-Version: 4.5.0 Vcs-Browser: https://salsa.debian.org/med-team/chromhmm Vcs-Git: https://salsa.debian.org/med-team/chromhmm.git Homepage: http://compbio.mit.edu/ChromHMM/ Rules-Requires-Root: no Package: chromhmm Architecture: all Depends: ${java:Depends}, ${misc:Depends} Recommends: ${java:Recommends} Description: Chromatin state discovery and characterization 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. Package: chromhmm-example Architecture: all Multi-Arch: foreign Section: doc Depends: ${misc:Depends} Enhances: chromhmm Description: Chromatin state discovery and characterization (example) 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. . This package provides example to work with ChromHMM.