Package: epigraHMM
Title: Epigenomic R-based analysis with hidden Markov models
Version: 1.4.0
Date: 2019-12-10
Authors@R: c(person("Pedro", "Baldoni", email = "pedrobaldoni@gmail.com", role = c("aut","cre")))
biocViews: ChIPSeq, ATACSeq, DNaseSeq, HiddenMarkovModel, Epigenetics
Description: 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.
License: MIT + file LICENSE
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
RoxygenNote: 7.1.2
Encoding: UTF-8
SystemRequirements: GNU make
Suggests: testthat, knitr, rmarkdown, BiocStyle,
        BSgenome.Rnorvegicus.UCSC.rn4, gcapc, chromstaRData
VignetteBuilder: knitr
LazyData: true
git_url: https://git.bioconductor.org/packages/epigraHMM
git_branch: RELEASE_3_15
git_last_commit: 82b8a69
git_last_commit_date: 2022-04-26
Date/Publication: 2022-04-26
NeedsCompilation: yes
Packaged: 2022-04-26 22:58:26 UTC; biocbuild
Author: Pedro Baldoni [aut, cre]
Maintainer: Pedro Baldoni <pedrobaldoni@gmail.com>
Depends: R (>= 3.5.0)
Built: R 4.2.0; x86_64-w64-mingw32; 2022-04-27 09:27:40 UTC; windows
ExperimentalWindowsRuntime: ucrt
Archs: x64
