News from the Bioconductor Project

The ‘News from the Bioconductor Project’ article from the 2010-2 issue.

Bioconductor Team (Program in Computational Biology, Fred Hutchinson Cancer Research Center)
2010-12-01

We are pleased to announce Bioconductor 2.7, released on October 18, 2010. Bioconductor 2.7 is compatible with R 2.12.0, and consists of 419 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 IRanges

1 New and revised packages

This release includes new packages for diverse areas of high-throughput analysis. Highlights include:

Next-generation sequencing

packages for ChIP (iSeq, RMAPPER), methylated DNA immunoprecipitation (MEDIPS), and RNA-seq (rnaSeqMap) work flows, 454 sequencing (R453Plus1Toolbox) and management of microbial sequences (OTUbase).

Microarray

analysis of domain-specific applications (array CGH, ADaCGH2; tiling arrays, les; miRNA, LVSmiRNA; and bead arrays, MBCB); specialized statistical methods (fabia, farms, RDRToolbox), and graphical tools (IsoGeneGUI).

Gene set, network, and graph

oriented approaches and tools include gage, HTSanalyzeR, PatientGeneSets, BioNet, netresponse, attract, CoGAPS, ontoCAT, DEgraph, NTW, and RCytoscape.

Advanced statistical and modeling implementations

relevant to high-throughtput genetic analysis include BHC (Bayesian Hierarchical Clustering), CGEN (case-control studies in genetic epidemiology), and SQUADD.

Image, cell-based, and other assay

packages, include imageHTS, CRImage, coRNAi, GeneGA, NuPoP.

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.

Several developments in packages maintained by the Bioconductor core team are noteworthy. The graphBAM class in the graph package is available to manipulate very large graphs. The GenomicRanges, GenomicFeatures, and Biostrings packages have enhanced classes such as TranscriptDb for representing genome-scale ‘track’ annotations from common data resources, MultipleAlignment for manipulating reference (and other moderate-length) sequences in a microbiome project, and SummarizedExperiment to collate range-based count data across samples in sequence experiments. The chipseq package has enhanced functionality for peak calling, and has been updated to use current data structures.

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.

2 Other activities

The Bioconductor community met on July 28-30 at our annual conference in Seattle for a combination of scientific talks and hands-on tutorials, and on November 17-18 in Heidelberg, Germany for a meeting highlight contributions from the European developer community. 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.

3 Looking forward

Contributions from the Bioconductor community play an important role in shaping each release. We anticipate continued efforts to provide statistically informed analysis of next generation sequence data, especially in the down-stream analysis of comprehensive, designed sequencing experiments and integrative analyses. The next release cycle promises to be one of active scientific growth and exploration.

Bioconductor packages used

iSeq, RMAPPER, MEDIPS, rnaSeqMap, R453Plus1Toolbox, OTUbase, ADaCGH2, les, LVSmiRNA, MBCB, fabia, farms, RDRToolbox, IsoGeneGUI, gage, HTSanalyzeR, PatientGeneSets, BioNet, netresponse, attract, CoGAPS, ontoCAT, DEgraph, NTW, RCytoscape, BHC, CGEN, SQUADD, imageHTS, CRImage, coRNAi, GeneGA, NuPoP, graph, GenomicRanges, GenomicFeatures, Biostrings, chipseq

Note

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Citation

For attribution, please cite this work as

Team, "News from the Bioconductor Project", The R Journal, 2010

BibTeX citation

@article{RJ-2010-2-bioconductor,
  author = {Team, Bioconductor},
  title = {News from the Bioconductor Project},
  journal = {The R Journal},
  year = {2010},
  note = {https://rjournal.github.io/},
  volume = {2},
  issue = {2},
  issn = {2073-4859},
  pages = {101-101}
}