To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("STAN")

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

STAN

 

   

The genomic STate ANnotation package

Bioconductor version: Release (3.4)

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: Benedikt Zacher <zacher at genzentrum.lmu.de>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("STAN")

Documentation

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

browseVignettes("STAN")

 

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

Details

biocViews ChIPSeq, ChipOnChip, GenomeAnnotation, HiddenMarkovModel, Microarray, RNASeq, Sequencing, Software, Transcription
Version 2.2.0
In Bioconductor since BioC 3.0 (R-3.1) (2.5 years)
License GPL (>= 2)
Depends methods, poilog, parallel
Imports GenomicRanges, IRanges, S4Vectors, BiocGenerics, GenomeInfoDb, Gviz, Rsolnp
LinkingTo
Suggests BiocStyle, gplots, knitr
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source STAN_2.2.0.tar.gz
Windows Binary STAN_2.2.0.zip (32- & 64-bit)
Mac OS X 10.9 (Mavericks) STAN_2.2.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/STAN/tree/release-3.4
Package Short Url http://bioconductor.org/packages/STAN/
Package Downloads Report Download Stats

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