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epigraHMM

This is thereleased version of epigraHMM; for the devel version, seeepigraHMM.

Epigenomic R-based analysis with hidden Markov models

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DOI: 10.18129/B9.bioc.epigraHMM


Bioconductor version: Release (3.22)

epigraHMM provides a set of tools for the analysis of epigenomic data based on hidden Markov Models. It contains two separate peak callers, one for consensus peaks from biological or technical replicates, and one for differential peaks from multi-replicate multi-condition experiments. In differential peak calling, epigraHMM provides window-specific posterior probabilities associated with every possible combinatorial pattern of read enrichment across conditions.

Author: Pedro Baldoni [aut, cre]

Maintainer: Pedro Baldoni <pedrobaldoni at gmail.com>

Citation (from within R, entercitation("epigraHMM")):

Installation

To install this package, start R (version "4.5") and enter:

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

For older versions of R, please refer to the appropriateBioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("epigraHMM")
Consensus and Differential Peak Calling With epigraHMMHTMLR Script
Reference ManualPDF
NEWSText
LICENSEText

Need some help? Ask on the Bioconductor Support site!

Details

biocViewsATACSeq,ChIPSeq,DNaseSeq,Epigenetics,HiddenMarkovModel,Software
Version1.18.0
In Bioconductor sinceBioC 3.13 (R-4.1) (4.5 years)
LicenseMIT + fileLICENSE
DependsR (>= 3.5.0)
ImportsRcpp,magrittr,data.table,SummarizedExperiment, methods,Seqinfo,GenomicRanges,rtracklayer,IRanges,Rsamtools,bamsignals,csaw,S4Vectors,limma, stats,Rhdf5lib,rhdf5,Matrix,MASS,scales,ggpubr,ggplot2,GreyListChIP,pheatmap, grDevices
System RequirementsGNU make
URL
See More
SuggestsGenomeInfoDb,testthat,knitr,rmarkdown,BiocStyle,BSgenome.Rnorvegicus.UCSC.rn4,gcapc,chromstaRData
Linking ToRcpp,RcppArmadillo,Rhdf5lib
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build ReportBuild Report

Package Archives

FollowInstallation instructions to use this package in your R session.

Source PackageepigraHMM_1.18.0.tar.gz
Windows Binary (x86_64) epigraHMM_1.18.0.zip (64-bit only)
macOS Binary (x86_64)epigraHMM_1.18.0.tgz
macOS Binary (arm64)epigraHMM_1.18.0.tgz
Source Repositorygit clone https://git.bioconductor.org/packages/epigraHMM
Source Repository (Developer Access)git clone git@git.bioconductor.org:packages/epigraHMM
Bioc Package Browserhttps://code.bioconductor.org/browse/epigraHMM/
Package Short Urlhttps://bioconductor.org/packages/epigraHMM/
Package Downloads ReportDownload Stats

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