To install this package, start R and enter:

## try http:// if https:// URLs are not supported

In most cases, you don't need to download the package archive at all.


DOI: 10.18129/B9.bioc.STAN    

This is the development version of STAN; for the stable release version, see STAN.

The Genomic STate ANnotation Package

Bioconductor version: Development (3.6)

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).

Author: Benedikt Zacher, Julia Ertl, Julien Gagneur, Achim Tresch

Maintainer: Rafael Campos-Martin <campos at>

Citation (from within R, enter citation("STAN")):


To install this package, start R and enter:

## try http:// if https:// URLs are not supported


To view documentation for the version of this package installed in your system, start R and enter:



PDF R Script The genomic STate ANnotation package
PDF   Reference Manual
Text   NEWS


biocViews ChIPSeq, ChipOnChip, GenomeAnnotation, HiddenMarkovModel, Microarray, RNASeq, Sequencing, Software, Transcription
Version 2.5.1
In Bioconductor since BioC 3.0 (R-3.1) (3 years)
License GPL (>= 2)
Depends methods, poilog, parallel
Imports GenomicRanges, IRanges, S4Vectors, BiocGenerics, GenomeInfoDb, Gviz, Rsolnp
Suggests BiocStyle, gplots, knitr
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package STAN_2.5.1.tar.gz
Windows Binary (32- & 64-bit)
Mac OS X 10.11 (El Capitan) STAN_1.0.0.tgz
Source Repository git clone
Package Short Url
Package Downloads Report Download Stats

Documentation »


R / CRAN packages and documentation

Support »

Please read the posting guide. Post questions about Bioconductor to one of the following locations: