STAN: The Genomic STate ANnotation Package

Genome segmentation with hidden Markov models has become a useful tool to annotate genomic elements, such as promoters and enhancers. STAN (genomic STate ANnotation) implements (bidirectional) hidden Markov models (HMMs) using a variety of different probability distributions, which can model a wide range of current genomic data (e.g. continuous, discrete, binary). STAN de novo learns and annotates the genome into a given number of 'genomic states'. The 'genomic states' may for instance reflect distinct genome-associated protein complexes (e.g. 'transcription states') or describe recurring patterns of chromatin features (referred to as 'chromatin states'). Unlike other tools, STAN also allows for the integration of strand-specific (e.g. RNA) and non-strand-specific data (e.g. ChIP).

Package details

AuthorBenedikt Zacher, Julia Ertl, Rafael Campos-Martin, Julien Gagneur, Achim Tresch
Bioconductor views ChIPSeq ChipOnChip GenomeAnnotation HiddenMarkovModel ImmunoOncology Microarray RNASeq Sequencing Transcription
MaintainerRafael Campos-Martin <>
LicenseGPL (>= 2)
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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STAN documentation built on Nov. 8, 2020, 11:11 p.m.