This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see STAN.
Bioconductor version: 3.15
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")
):
To install this package, start R (version "4.2") 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.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("STAN")
R Script | The genomic STate ANnotation package | |
Reference Manual |
biocViews | ChIPSeq, ChipOnChip, GenomeAnnotation, HiddenMarkovModel, ImmunoOncology, Microarray, RNASeq, Sequencing, Software, Transcription |
Version | 2.24.0 |
In Bioconductor since | BioC 3.0 (R-3.1) (8 years) |
License | GPL (>= 2) |
Depends | R (>= 3.5.0), 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 |
Follow Installation instructions to use this package in your R session.
Source Package | STAN_2.24.0.tar.gz |
Windows Binary | STAN_2.24.0.zip |
macOS Binary (x86_64) | STAN_2.24.0.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 | https://bioconductor.org/packages/STAN/ |
Package Downloads Report | Download Stats |
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