The ‘News from the Bioconductor Project’ article from the 2016-2 issue.
The Bioconductor project provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor 3.4 was released on 18 October, 2016. It is compatible with R 3.3 and consists of 1296 software packages, 309 experiment data packages, and 933 up-to-date annotation packages. The release announcement includes descriptions of 101 new packages, and updated NEWS files for many additional packages. Start using Bioconductor by installing the most recent version of R and evaluating the commands
source("https://bioconductor.org/biocLite.R")
biocLite()Install additional packages and dependencies, e.g., AnnotationHub, with
BiocInstaller::biocLite("AnnotationHub")Docker and Amazon images provide a very effective on-ramp for power users to rapidly obtain access to standardized and scalable computing environments. Key resources include:
bioconductor.org to install, learn, use, and develop Bioconductor packages.
A listing of available software, linked to pages describing each package.
A question-and-answer style user support site and developer-oriented mailing list.
The F1000Research Bioconductor channel for peer-reviewed Bioconductor work flows.
Our package submission repository for open technical review of new packages.
Our annual conference, BioC 2017: Where Software and Biology Connect, will be on June 26 (‘developer day’), 27 and 28, in Boston, MA.
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For attribution, please cite this work as
Team, "News from the Bioconductor Project", The R Journal, 2016
BibTeX citation
@article{RJ-2016-2-bioc,
author = {Team, Bioconductor Core},
title = {News from the Bioconductor Project},
journal = {The R Journal},
year = {2016},
note = {https://rjournal.github.io/},
volume = {8},
issue = {2},
issn = {2073-4859},
pages = {510-510}
}