STAN: The genomic STate ANnotation package

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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
Date of publication
None
Maintainer
Benedikt Zacher <zacher@genzentrum.lmu.de>
License
GPL (>= 2)
Version
2.2.0

View on Bioconductor

Man pages

bdHMM
Create a bdHMM object
bdHMM-class
This class is a generic container for bidirectional Hidden...
binarizeData
Binarize Sequencing data with the default ChromHMM...
c2optimize
Optimize transitions
call_dpoilog
Calculate density of the Poisson-Log-Normal distribution.
data2Gviz
Convert data for plotting with Gviz
DimNames
Get dimNames of a (bd)HMM
DirScore
Get directionality score of a bdHMM
Emission
Get Emission functions of a (bd)HMM
EmissionParams
Get Emission parameters of a (bd)HMM.
example
The data for the bdHMM example in the vignette and examples...
fitHMM
Fit a Hidden Markov Model
flags
Pre-computed flag sequence for the 'example' data.
getAvgSignal
Compute average signal in state segmentation
getLogLik
Calculate log likelihood state distribution.
getPosterior
Calculate posterior state distribution.
getSizeFactors
Compute size factors
getViterbi
Calculate the most likely state path
HMM
Create a HMM object
HMM-class
This class is a generic container for Hidden Markov Models.
HMMEmission
Create a HMMEmission object
HMMEmission-class
This class is a generic container for different emission...
initBdHMM
Initialization of bidirectional hidden Markov models
initHMM
Initialization of hidden Markov models
InitProb
Get initial state probabilities of a (bd)HMM
LogLik
Get stateNames of a (bd)HMM
observations
Observation sequence for the 'example' data.
pilot.hg19
Genomic positions of processed signal for the Roadmap...
runningMean
Smooth data with running mean
STAN-package
The genomic STate ANnotation package
StateNames
Get stateNames of a (bd)HMM
sub-bdHMM-ANY-ANY-method
This function subsets a bdHMM object. Rows are interpreted as...
sub-HMM-ANY-ANY-method
This function subsets an HMM object. Rows are interpreted as...
trainRegions
Training regions for the Roadmap Epigenomics data set. Three...
Transitions
Get transitions of a (bd)HMM
ucscGenes
UCSC gene annotation for the Roadmap Epigenomics data set.
viterbi2GRanges
Convert the viterbi path to a GRanges object
viterbi2Gviz
Convert state segmentation for plotting with Gviz
yeastTF_databychrom_ex
Processed ChIP-on-chip data for yeast TF example
yeastTF_SGDGenes
SGD annotation for the yeast TF example

Files in this package

STAN/DESCRIPTION
STAN/NAMESPACE
STAN/R
STAN/R/AllClasses.R
STAN/R/STAN-package.R
STAN/R/bdConstraints.R
STAN/R/bdHMMTransMatOptim.R
STAN/R/fitHMM.R
STAN/R/getLogLik.R
STAN/R/getPosterior.R
STAN/R/getViterbi.R
STAN/R/initBdHMM.R
STAN/R/initHMM.R
STAN/R/optimizeNB.R
STAN/R/optimizePoilog.R
STAN/R/utils.R
STAN/build
STAN/build/vignette.rds
STAN/data
STAN/data/example.rda
STAN/data/pilot.hg19.rda
STAN/data/trainRegions.rda
STAN/data/ucscGenes.rda
STAN/data/yeastTF_SGDGenes.rda
STAN/data/yeastTF_databychrom_ex.rda
STAN/inst
STAN/inst/CITATION
STAN/inst/NEWS
STAN/inst/doc
STAN/inst/doc/STAN.R
STAN/inst/doc/STAN.Rnw
STAN/inst/doc/STAN.pdf
STAN/man
STAN/man/DimNames.Rd
STAN/man/DirScore.Rd
STAN/man/Emission.Rd
STAN/man/EmissionParams.Rd
STAN/man/HMM-class.Rd
STAN/man/HMM.Rd
STAN/man/HMMEmission-class.Rd
STAN/man/HMMEmission.Rd
STAN/man/InitProb.Rd
STAN/man/LogLik.Rd
STAN/man/STAN-package.Rd
STAN/man/StateNames.Rd
STAN/man/Transitions.Rd
STAN/man/bdHMM-class.Rd
STAN/man/bdHMM.Rd
STAN/man/binarizeData.Rd
STAN/man/c2optimize.Rd
STAN/man/call_dpoilog.Rd
STAN/man/data2Gviz.Rd
STAN/man/example.Rd
STAN/man/fitHMM.Rd
STAN/man/flags.Rd
STAN/man/getAvgSignal.Rd
STAN/man/getLogLik.Rd
STAN/man/getPosterior.Rd
STAN/man/getSizeFactors.Rd
STAN/man/getViterbi.Rd
STAN/man/initBdHMM.Rd
STAN/man/initHMM.Rd
STAN/man/observations.Rd
STAN/man/pilot.hg19.Rd
STAN/man/runningMean.Rd
STAN/man/sub-HMM-ANY-ANY-method.Rd
STAN/man/sub-bdHMM-ANY-ANY-method.Rd
STAN/man/trainRegions.Rd
STAN/man/ucscGenes.Rd
STAN/man/viterbi2GRanges.Rd
STAN/man/viterbi2Gviz.Rd
STAN/man/yeastTF_SGDGenes.Rd
STAN/man/yeastTF_databychrom_ex.Rd
STAN/src
STAN/src/Bernoulli.cpp
STAN/src/Bernoulli.h
STAN/src/BernoulliFactory.h
STAN/src/DebugConstants.h
STAN/src/EmissionFactory.cpp
STAN/src/EmissionFactory.h
STAN/src/EmissionFunction.cpp
STAN/src/EmissionFunction.h
STAN/src/HMM.cpp
STAN/src/HMM.h
STAN/src/InitialProbability.cpp
STAN/src/InitialProbability.h
STAN/src/JointlyIndependent.cpp
STAN/src/JointlyIndependent.h
STAN/src/JointlyIndependentFactory.h
STAN/src/Makevars
STAN/src/MemoryAllocation.cpp
STAN/src/MemoryAllocation.h
STAN/src/Multinomial.cpp
STAN/src/Multinomial.h
STAN/src/MultinomialFactory.h
STAN/src/MultivariateGaussian.cpp
STAN/src/MultivariateGaussian.h
STAN/src/MultivariateGaussianFactory.h
STAN/src/NegativeBinomial.cpp
STAN/src/NegativeBinomial.h
STAN/src/NegativeBinomialFactory.h
STAN/src/ParamContainerEmissions.cpp
STAN/src/ParamContainerEmissions.h
STAN/src/Poisson.cpp
STAN/src/Poisson.h
STAN/src/PoissonFactory.h
STAN/src/PoissonLogNormal.cpp
STAN/src/PoissonLogNormal.h
STAN/src/PoissonLogNormalFactory.h
STAN/src/RAccessUtils.cpp
STAN/src/RAccessUtils.h
STAN/src/RWrapper.cpp
STAN/src/RWrapper.h
STAN/src/TransitionMatrix.cpp
STAN/src/TransitionMatrix.h
STAN/src/matUtils.cpp
STAN/src/matUtils.h
STAN/vignettes
STAN/vignettes/STAN.Rnw
STAN/vignettes/refs.bib