The ‘News from the Bioconductor Project’ article from the 2009-2 issue.
We are pleased to announce Bioconductor 2.5, released on October 28, 2009. Bioconductor 2.5 is compatible with R 2.10.0, and consists of 352 packages. There are 34 new packages, and enhancements to many others. Explore Bioconductor at http://bioconductor.org, and install packages with
> source("http://bioconductor.org/biocLite.R")
> biocLite() # install standard packages...
> biocLite("IRanges") # ...or IRangesThis release includes new packages for diverse areas of high-throughput analysis. Highlights include:
packages for ChIP-seq (chipseq, ChIPseqR, chIPpeakAnno, ChIPsim), differential expression (DEGseq, baySeq), annotation (GenomicFeatures), and image processing (Rolexa).
for microarray classification (BioSeqClass), differential expression (cycle, LiquidAssociation, SpeCond), and probe reliability (RPA).
of copy number, array CGH, tiling (CNTools, CNVtools, Starr, CGHnormaliter, mBPCR), micro-RNA (AgiMicroRna, RmiR, MiChip), and methylation (methylumi) arrays.
fingerprinting (flowFP), cluster merging (flowMerge), and plate-based assays (plateCore).
related to high-throughput qPCR (ddCt, HTqPCR), clinical proteomics (clippda), and RTCA (RTCA).
for data mining (RTools4TB), annotation (GeneAnswers), network reconstruction (BUS), and visualization (ChromHeatMap).
Our large collection of microarray- and organism-specific annotation packages have been updated to include information current at the time of the Bioconductor release. These annotation packages contain biological information about microarray probes and the genes they are meant to interrogate, or contain gene-based annotations of whole genomes. They are particularly valuable in providing stable annotations for repeatable research.
Further information on new and existing packages can be found on the Bioconductor web site, which contains ‘views’ that identify coherent groups of packages. The views link to on-line package descriptions, vignettes, reference manuals, and use statistics.
The Bioconductor community met on July 27-28 at our annual conference in Seattle for a combination of scientific talks and hands-on tutorials. The active Bioconductor mailing lists (http://bioconductor.org/docs/mailList.html) connect users with each other, to domain experts, and to maintainers eager to ensure that their packages satisfy the needs of leading edge approaches. Bioconductor package maintainers and the Bioconductor team invest considerable effort in producing high-quality software. The Bioconductor team continues to ensure quality software through technical and scientific reviews of new packages, and daily builds of released packages on Linux, Windows, and Macintosh platforms.
Contributions from the Bioconductor community play an important role in shaping each release. In addition to development of high-quality algorithms for microarray data, we anticipate continued efforts to provide statistically informed analysis of next generation sequence data. Areas of opportunity include the ChIP-seq, RNA-seq, rare variant, and structural variant domains. Analysis of next generation sequence data poses significant challenges in data representation, annotation, and manipulation; the Bioconductor team is actively working on solutions to address these software infrastructure challenges. We also anticipate development of improved graph representations, important for manipulating large networks of biological data. The next release cycle promises to be one of active scientific growth and exploration!
chipseq, ChIPseqR, chIPpeakAnno, ChIPsim, DEGseq, baySeq, GenomicFeatures, Rolexa, BioSeqClass, cycle, LiquidAssociation, SpeCond, RPA, CNTools, CNVtools, Starr, CGHnormaliter, mBPCR, AgiMicroRna, RmiR, MiChip, methylumi, flowFP, flowMerge, plateCore, ddCt, HTqPCR, clippda, RTCA, RTools4TB, GeneAnswers, BUS, ChromHeatMap
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For attribution, please cite this work as
Team, "News from the Bioconductor Project", The R Journal, 2009
BibTeX citation
@article{RJ-2009-2-bioconductor,
author = {Team, Bioconductor},
title = {News from the Bioconductor Project},
journal = {The R Journal},
year = {2009},
note = {https://rjournal.github.io/},
volume = {1},
issue = {2},
issn = {2073-4859},
pages = {95-95}
}