Package: epigraHMM 1.20.2

Pedro Baldoni

epigraHMM: Epigenomic R-based analysis with hidden Markov models

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.

Authors:Pedro Baldoni [aut, cre]

epigraHMM_1.20.2.tar.gz
epigraHMM_1.20.2.zip(r-4.7)epigraHMM_1.20.2.zip(r-4.6)epigraHMM_1.20.2.zip(r-4.5)
epigraHMM_1.20.2.tgz(r-4.6-x86_64)epigraHMM_1.20.2.tgz(r-4.6-arm64)epigraHMM_1.20.2.tgz(r-4.5-x86_64)epigraHMM_1.20.2.tgz(r-4.5-arm64)
epigraHMM_1.20.2.tar.gz(r-4.7-arm64)epigraHMM_1.20.2.tar.gz(r-4.7-x86_64)epigraHMM_1.20.2.tar.gz(r-4.6-arm64)epigraHMM_1.20.2.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
card.svg |card.png
epigraHMM/json (API)
NEWS

# Install 'epigraHMM' in R:
install.packages('epigraHMM', repos = c('https://bioc-release.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • curl– Easy-to-use client-side URL transfer library
  • openssl– Secure Sockets Layer toolkit
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • helas3 - ENCODE ChIP-seq broad data from Helas3 cell line

On BioConductor:epigraHMM-1.21.2(bioc 3.24)epigraHMM-1.20.2(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

chipseqatacseqdnaseseqhiddenmarkovmodelepigeneticscurlopensslopenblascppopenmp

5.55 score 89 scripts 292 downloads 18 exports 135 dependencies

Last updated from:285c65e0d3 (on RELEASE_3_23). Checks:1 WARNING, 12 OK, 1 FAIL. Indexed: no.

TargetResultTimeFilesSyslog
bioc-checksWARNING350
linux-devel-arm64OK545
linux-devel-x86_64OK697
source / vignettesOK907
linux-release-arm64OK561
linux-release-x86_64OK642
macos-release-arm64OK347
macos-release-x86_64OK832
macos-oldrel-arm64OK396
macos-oldrel-x86_64OK853
windows-develOK633
windows-releaseOK652
windows-oldrelOK639
wasm-releaseFAIL283

Exports:addOffsetscallPatternscallPeakscleanCountscontrolEMepigraHMMepigraHMMDataSetFromBamepigraHMMDataSetFromMatrixestimateTransitionProbexpStepinfoinitializermaxStepProbnormalizeCountsplotCountsplotPatternssegmentGenomesimulateMarkovChain

Dependencies:abindaskpassbackportsBHBiobaseBiocGenericsBiocIObiocmakeBiocParallelBiostringsbitopsbootbroomBSgenomecarcarDatacigarilloclicodetoolscolorspacecorrplotcowplotcpp11crayoncsawcurldata.tableDelayedArrayDerivdir.expirydoBydplyredgeRfarverfilelockforecastformatRFormulafracdifffutile.loggerfutile.optionsgenericsGenomicAlignmentsGenomicRangesggplot2ggpubrggrepelggsciggsignifglueGreyListChIPgridExtragtablehttrIRangesisobandjsonlitelabelinglambda.rlatticelifecyclelimmalme4lmtestlocfitmagrittrMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmetapodmgcvmicrobenchmarkmimeminqamodelrnlmenloptrnnetnumDerivopensslpbkrtestpheatmappillarpkgconfigpolynompurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRCurlRdpackreformulasrestfulrrhdf5rhdf5filtersRhdf5libRhtslibrjsonrlangRsamtoolsrstatixrtracklayerS4ArraysS4VectorsS7scalesSeqinfosnowSparseArraySparseMstatmodstringistringrSummarizedExperimentsurvivalsystibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrXMLXVectoryamlzoo

Consensus and differential peak calling with epigraHMM

Pedro L. Baldoni, Naim U. Rashid, Joseph G. Ibrahim

Rendered fromepigraHMM.Rmdusingknitr::rmarkdownon Jun 12 2026.

Last update: 2026-05-12
Started: 2021-03-01