STAN

DOI: 10.18129/B9.bioc.STAN    

This package is for version 3.7 of Bioconductor; for the stable, up-to-date release version, see STAN.

The Genomic STate ANnotation Package

Bioconductor version: 3.7

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 mpipz.mpg.de>

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	2.8.0
In Bioconductor since	BioC 3.0 (R-3.1) (4 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
Links To Me
Build Report

Package Archives

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

Source Package	STAN_2.8.0.tar.gz
Windows Binary	STAN_2.8.0.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan)	STAN_2.8.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/STAN
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/STAN
Package Short Url	http://bioconductor.org/packages/STAN/
Package Downloads Report	Download Stats