Bioconductor version: Release (3.15)
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,
enter citation("epigraHMM")
):
To install this package, start R (version "4.2") 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.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("epigraHMM")
HTML | R Script | Consensus and Differential Peak Calling With epigraHMM |
Reference Manual | ||
Text | NEWS | |
Text | LICENSE |
biocViews | ATACSeq, ChIPSeq, DNaseSeq, Epigenetics, HiddenMarkovModel, Software |
Version | 1.4.0 |
In Bioconductor since | BioC 3.13 (R-4.1) (1.5 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 |
LinkingTo | Rcpp, RcppArmadillo, Rhdf5lib |
Suggests | testthat, knitr, rmarkdown, BiocStyle, BSgenome.Rnorvegicus.UCSC.rn4, gcapc, chromstaRData |
SystemRequirements | GNU make |
Enhances | |
URL | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | epigraHMM_1.4.0.tar.gz |
Windows Binary | epigraHMM_1.4.0.zip |
macOS Binary (x86_64) | epigraHMM_1.4.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/epigraHMM |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/epigraHMM |
Package Short Url | https://bioconductor.org/packages/epigraHMM/ |
Package Downloads Report | Download Stats |
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