STAN

This package is for version 3.9 of Bioconductor. This package has been removed from Bioconductor. For the last stable, up-to-date release version, see STAN.

The Genomic STate ANnotation Package


Bioconductor version: 3.9

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, Rafael Campos-Martin, Julien Gagneur, Achim Tresch

Maintainer: Rafael Campos-Martin <campos at mpipz.mpg.de>

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

Installation

To install this package, start R (version "3.6") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("STAN")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

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

browseVignettes("STAN")
The genomic STate ANnotation package PDF R Script
Reference Manual PDF

Details

biocViews ChIPSeq, ChipOnChip, GenomeAnnotation, HiddenMarkovModel, ImmunoOncology, Microarray, RNASeq, Sequencing, Software, Transcription
Version 2.12.0
In Bioconductor since BioC 3.0 (R-3.1) (9.5 years)
License GPL (>= 2)
Depends methods, poilog, parallel
Imports GenomicRanges, IRanges, S4Vectors, BiocGenerics, GenomeInfoDb, Gviz, Rsolnp
System Requirements
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Suggests BiocStyle, gplots, knitr
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Package Archives

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

Source Package STAN_2.12.0.tar.gz
Windows Binary STAN_2.12.0.zip
Mac OS X 10.11 (El Capitan) STAN_2.12.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/STAN
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/STAN
Bioc Package Browser https://code.bioconductor.org/browse/STAN/
Package Short Url https://bioconductor.org/packages/STAN/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.9 Source Archive