epigraHMM
Epigenomic R-based analysis with hidden Markov models
Bioconductor version: Release (3.20)
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("epigraHMM")
):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("epigraHMM")
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("epigraHMM")
Consensus and Differential Peak Calling With epigraHMM | HTML | R Script |
Reference Manual | ||
NEWS | Text | |
LICENSE | Text |
Details
biocViews | ATACSeq, ChIPSeq, DNaseSeq, Epigenetics, HiddenMarkovModel, Software |
Version | 1.14.0 |
In Bioconductor since | BioC 3.13 (R-4.1) (3.5 years) |
License | MIT + file LICENSE |
Depends | R (>= 3.5.0) |
Imports | Rcpp, magrittr, data.table, SummarizedExperiment, methods, GenomeInfoDb, GenomicRanges, rtracklayer, IRanges, Rsamtools, bamsignals, csaw, S4Vectors, limma, stats, Rhdf5lib, rhdf5, Matrix, MASS, scales, ggpubr, ggplot2, GreyListChIP, pheatmap, grDevices |
System Requirements | GNU make |
URL |
See More
Suggests | testthat, knitr, rmarkdown, BiocStyle, BSgenome.Rnorvegicus.UCSC.rn4, gcapc, chromstaRData |
Linking To | Rcpp, RcppArmadillo, Rhdf5lib |
Enhances | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | epigraHMM_1.14.0.tar.gz |
Windows Binary (x86_64) | epigraHMM_1.14.0.zip |
macOS Binary (x86_64) | epigraHMM_1.14.0.tgz |
macOS Binary (arm64) | epigraHMM_1.13.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/epigraHMM |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/epigraHMM |
Bioc Package Browser | https://code.bioconductor.org/browse/epigraHMM/ |
Package Short Url | https://bioconductor.org/packages/epigraHMM/ |
Package Downloads Report | Download Stats |