tileHMM: Hidden Markov Models for ChIP-on-Chip Analysis
Version 1.0-7

Methods and classes to build HMMs that are suitable for the analysis of ChIP-chip data. The provided parameter estimation methods include the Baum-Welch algorithm and Viterbi training as well as a combination of both.

AuthorPeter Humburg [aut, cre]
Date of publication2015-07-03 00:25:58
MaintainerPeter Humburg <peter.humburg@gmail.com>
LicenseGPL (>= 2)
Version1.0-7
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("tileHMM")

Getting started

Package overview
README.md

Popular man pages

forward: Computation of Forward and Backward Variables
getHMM: Create HMM from Parameter Values
hmm-class: Class "hmm"
region.length: Determine Length of Positive and Negative Regions
sampleSeq: Generate Observation Sequence from HMM
simChIP: Simulated ChIP-on-Chip Data
viterbi: Calculate Most Likely State Sequence Using the Viterbi...
See all...

All man pages Function index File listing

Man pages

baumWelch: Baum-Welch Algorithm
contDist-class: Class "contDist"
contHMM-access: Accessing Objects of Class "contHMM"
contHMM-class: Class "contHMM"
discDist-class: Class "discDist"
dist-access: Accessing and Converting Objects of Class "dist"
dist-class: Class "dist"
forward: Computation of Forward and Backward Variables
generate.data: Generate Simulated Dataset
getHMM: Create HMM from Parameter Values
gff2index: Extract Probe Calls from GFF File
hmm-class: Class "hmm"
hmm.setup: Create HMM from Initial Parameter Estimates Obtained from...
initializeDist-methods: Generating Objects of Class 'dist'
initializeHMM-methods: Generate Objects of Class 'hmm'
internals: Internal Functions
logSum: Calculate log(x + y) from log(x) and log(y)
plot: Plotting of "contDist" Objects
posterior: Calculate Posterior Probability for States of HMM
reg2gff: Converting Information about Enriched Regions into GFF Format
region.length: Determine Length of Positive and Negative Regions
region.position: Identify Enriched Regions
remove.short: Post-Processing of "tileHMM" Results
sampleObs: Sample Observations from Probability Distribution
sampleSeq: Generate Observation Sequence from HMM
shrinkt.st: Calculate 'Shrinkage t' Statistic
simChIP: Simulated ChIP-on-Chip Data
states: State Names of Hidden Markov Model
tDist-class: Class "tDist"
tileHMM-package: Hidden Markov Models for ChIP-on-Chip Analysis
viterbi: Calculate Most Likely State Sequence Using the Viterbi...
viterbiEM: Efficient Estimation of HMM Parameters
viterbiTraining: Estimate HMM Parameters Using Viterbi Training

Functions

.baumWelchEmission,contHMM,contDist,list-method Man page Man page
.baumWelchEmission,contHMM,tDist,list-method Man page
.baumWelchStep,contHMM,list-method Man page
.viterbiTrainingEmission,contHMM,list,list-method Man page
[.contDist Man page
[.contHMM Man page
[.discDist Man page
[.tDist Man page
[<-.contDist Man page
[<-.tDist Man page
[[.discDist Man page
_backward Man page
_baumWelch_trans Man page
_forward Man page
_get_obs_prob Man page
_log_sum Man page
_viterbi Man page
as.data.frame.discDist Man page Source code
as.matrix.discDist Man page Source code
as.vector.discDist Man page Source code
backward Man page
backward,hmm-method Man page
baumWelch Man page
baumWelch,hmm,list-method Man page
baumWelchInit Source code
baumWelchTransition Source code
calcU Source code
contDist-class Man page
contHMM-access Man page
contHMM-class Man page
df.fun Source code
discDist-class Man page
dist-class Man page
find.df Source code
forward Man page
forward,hmm-method Man page
generate.data Man page Source code
get.init Source code
getHMM Man page Source code
gff2index Man page Source code
hmm-class Man page
hmm.setup Man page Source code
initialize,contDist-method Man page
initialize,contHMM Man page
initialize,contHMM-method Man page
initialize,discDist-method Man page
initialize,tDist-method Man page
internals Man page
length,discDist-method Man page
length,hmm-method Man page
logSum Man page Source code
new,contDist-method Man page
new,contHMM-method Man page
new,discDist-method Man page
new,tDist-method Man page
plot Man page
plot.contDist Man page Source code
plot.contHMM Man page Source code
plot.tDist Man page
posterior Man page Source code
reg2gff Man page Source code
region.length Man page Source code
region.position Man page Source code
remove.short Man page Source code
sampleObs Man page
sampleObs,discDist,numeric-method Man page Man page
sampleObs,tDist,numeric-method Man page
sampleSeq Man page
sampleSeq,contHMM,numeric-method Man page Man page
show,contDist-method Man page
show,hmm-method Man page
shrinkt.st Man page Source code
simChIP Man page
states Man page
states,hmm-method Man page
tDist-class Man page
tileHMM Man page
tileHMM-package Man page
viterbi Man page
viterbi,hmm-method Man page
viterbiEM Man page Source code
viterbiTraining Man page
viterbiTraining,hmm,list-method Man page

Files

inst
inst/COPYING
inst/CITATION
inst/doc
inst/doc/tileHMM.pdf
inst/doc/tileHMM.Rnw
inst/doc/tileHMM.R
src
src/tilehmm_lib.c
src/tilehmm_lib.h
NAMESPACE
NEWS.md
data
data/simChIP.rda
data/datalist
R
R/utils.R
R/hmm.R
R/dist.R
vignettes
vignettes/tileHMM.Rnw
README.md
MD5
build
build/vignette.rds
DESCRIPTION
man
man/states.Rd
man/remove.short.Rd
man/forward.Rd
man/dist-class.Rd
man/viterbiEM.Rd
man/tileHMM-package.Rd
man/hmm-class.Rd
man/reg2gff.Rd
man/viterbiTraining.Rd
man/getHMM.Rd
man/dist-access.Rd
man/viterbi.Rd
man/logSum.Rd
man/tDist-class.Rd
man/contHMM-class.Rd
man/simChIP.Rd
man/hmm.setup.Rd
man/region.length.Rd
man/internals.Rd
man/initializeHMM-methods.Rd
man/contDist-class.Rd
man/initializeDist-methods.Rd
man/gff2index.Rd
man/sampleObs.Rd
man/shrinkt.st.Rd
man/generate.data.Rd
man/baumWelch.Rd
man/contHMM-access.Rd
man/posterior.Rd
man/plot.Rd
man/sampleSeq.Rd
man/region.position.Rd
man/discDist-class.Rd
tileHMM documentation built on May 20, 2017, 1:30 a.m.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs in the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.