hummingbird

This package is for version 3.19 of Bioconductor; for the stable, up-to-date release version, see hummingbird.

Bayesian Hidden Markov Model for the detection of differentially methylated regions


Bioconductor version: 3.19

A package for detecting differential methylation. It exploits a Bayesian hidden Markov model that incorporates location dependence among genomic loci, unlike most existing methods that assume independence among observations. Bayesian priors are applied to permit information sharing across an entire chromosome for improved power of detection. The direct output of our software package is the best sequence of methylation states, eliminating the use of a subjective, and most of the time an arbitrary, threshold of p-value for determining significance. At last, our methodology does not require replication in either or both of the two comparison groups.

Author: Eleni Adam [aut, cre], Tieming Ji [aut], Desh Ranjan [aut]

Maintainer: Eleni Adam <eadam002 at odu.edu>

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

Installation

To install this package, start R (version "4.4") and enter:


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

BiocManager::install("hummingbird")

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("hummingbird")
hummingbird HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Bayesian, BiomedicalInformatics, DNAMethylation, DifferentialExpression, DifferentialMethylation, GeneExpression, HiddenMarkovModel, Sequencing, Software
Version 1.14.0
In Bioconductor since BioC 3.12 (R-4.0) (4 years)
License GPL (>=2)
Depends R (>= 4.0)
Imports Rcpp, graphics, GenomicRanges, SummarizedExperiment, IRanges
System Requirements
URL
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Suggests knitr, rmarkdown, BiocStyle
Linking To Rcpp
Enhances
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Package Archives

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

Source Package hummingbird_1.14.0.tar.gz
Windows Binary (x86_64) hummingbird_1.14.0.zip
macOS Binary (x86_64) hummingbird_1.14.0.tgz
macOS Binary (arm64) hummingbird_1.14.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/hummingbird
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/hummingbird
Bioc Package Browser https://code.bioconductor.org/browse/hummingbird/
Package Short Url https://bioconductor.org/packages/hummingbird/
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