Bioconductor 3.22 Released

bsseq

This is the development version of bsseq; for the stable release version, see bsseq.

Analyze, manage and store whole-genome methylation data


Bioconductor version: Development (3.23)

A collection of tools for analyzing and visualizing whole-genome methylation data from sequencing. This includes whole-genome bisulfite sequencing and Oxford nanopore data.

Author: Kasper Daniel Hansen [aut, cre] ORCID iD ORCID: 0000-0003-0086-0687 , Peter Hickey [aut] ORCID iD ORCID: 0000-0002-8153-6258 , Hervé Pagès [ctb], Aaron Lun [ctb]

Maintainer: Kasper Daniel Hansen <kasperdanielhansen at gmail.com>

Citation (from within R, enter citation("bsseq")):

Installation

To install this package, start R (version "4.6") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("bsseq")

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

Documentation

Reference Manual PDF

Details

biocViews DNAMethylation, Software
Version 1.47.0
In Bioconductor since BioC 2.11 (R-2.15) (13 years)
License Artistic-2.0
Depends R (>= 4.0), methods, BiocGenerics, GenomicRanges(>= 1.41.5), SummarizedExperiment(>= 1.19.5)
Imports IRanges(>= 2.23.9), Seqinfo, scales, stats, parallel, tools, graphics, Biobase, locfit, gtools, data.table (>= 1.11.8), S4Vectors(>= 0.27.12), R.utils (>= 2.0.0), DelayedMatrixStats(>= 1.5.2), permute, limma, DelayedArray(>= 0.15.16), Rcpp, BiocParallel, BSgenome, Biostrings, utils, HDF5Array(>= 1.19.11), rhdf5, beachmat(>= 2.23.2)
System Requirements C++17
URL https://github.com/kasperdanielhansen/bsseq
Bug Reports https://github.com/kasperdanielhansen/bsseq/issues
See More
Suggests testthat, bsseqData, BiocStyle, rmarkdown, knitr, Matrix, doParallel, rtracklayer, BSgenome.Hsapiens.UCSC.hg38, batchtools
Linking To Rcpp, beachmat, assorthead(>= 1.1.4)
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/bsseq
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/bsseq
Package Short Url https://bioconductor.org/packages/bsseq/
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