[R-pkgs] Release of Bioconductor 1.3

From: A.J. Rossini <rossini_at_blindglobe.net>
Date: Thu 30 Oct 2003 - 11:49:21 EST

The Bioconductor core group would like to announce the 1.3 release of the Bioconductor software. There are many new packages as well as several major upgrades and fixes in older packages, and users are encouraged to check them out. Release 1.3 is intended to be operated with R version 1.8.X, which can be obtained at CRAN (http://cran.r-project.org/)

All packages from the 1.2 release are included. All current bug fixes have been applied, and most have upgraded and provide enhanced functionality. The following is an overview of the most important changes, additions, and upgrades:

   There have been many improvements to the affy package. There were    big speed and memory improvement of ReadAffy, read.affybatch,    justRMA. A mas5calls method was added to get Affymetrix's P/M/A    calls. Cel and Cdf classes are no longer supported. Function,    read.celfile and other Cel related methods and functions    removed. Most Cdf related functions have moved to the makecdfenv    package. Function read.probematrix added. It reads CEL files and    returns a matrix of PM, MM, or both. This function is more memory    efficient than read.affybatch. Also, affy no longer depends on the    affydata package. For this reason some examples have been moved    from affy vignettes to the affydata vignette. The previously    deprecated express function has been completely removed. Lastly,    most normalization routines for AffyBatches can now be called with    the parameter type which specifies whether the normalization should    be applied as a PM-only, MM-only, both PM and MM together or PM and    MM separately.

   New assessment was added: assessSpikeIn2. Examples of new feature: Local

   slopes are computes and ROC curves divided by overall expression.    Also, all functions that work for hgu95a spike in now also work for hgu133a

   spike in experiment

   Functions for handling data from Bioconductor Affymetrix annotation    data packages. Produces compact HTML and text reports including    experimental data and URL links to many online databases. Allows    searching biological metadata using various criteria.

   The generic function as.data.frame() now works on objects of class    exprSet. This lets one access the extensive modeling facilities    through formula offered by R and packages like 'nlm'.

   A package containing functions useful for analyzing data from    factorial designed microarray experiments.

   Classification using partial least squares (PLS), a popular    dimension reduction tool in chemometrics, in the context of    generalized linear regression based on a previous approach,    Iteratively ReWeighted Partial Least Squares (IRWPLS) by Marx    (1996). Both two-group and multi-group classifications are    incorporated. Firth's bias reduction procedure is also incorporated    to ensure more stable and finite regression coefficients.

   Graph/Network handling is greatly improved. There is tighter    integration between graph, RBGL and Rgraphviz. Colors and SubGraph    layouts are now supported in Rgraphviz. RBGL support includes    minimal spanning trees, both strong and weakly connected    components, and Dijkstra's shortest path algorithm. In graph,    enhancements in validity checking and representation have been    made. New classes have been established that will allow for general    representations of nodes and edges. Capabilities include adding or    deleting both nodes and edges, combining sets of nodes into a    single node. Unions, intersections and complements of graphs    defined on a common set of nodes. Joining of two graphs into a    single graph. Functions to compute indegree and outdegree.

   Substantial updates including support for more image analysis    programs, new background correction methods, single channel    normalization, support for import of exprSet and marrayNorm data    objects, improved support for design and contrast matrices, new    fitted model object class, within-gene multiple testing, Venn    diagrams and generally a move to a simpler command style at the    user level.

   A new package providing tools for working with probe sequence    information: calculate ATCG content, reverse, complement, mismatch    sequences; fast exact sequence matching; combine AffyBatches of    different chip types; create probe data packages.

   A package to fit a two-level measurement error model for estimation    of correlation coefficient between two random variables assuming    bivariate normality for both the true value and measurement    error. This model allows dependence between measurement errors    hence is more flexible.

   Software for working with ontologies (structured vocabularies) and    their associations with general data resources.

   Generic framework for database access in R. Adapted from Rdbi    authored by Timothy H. Keitt, with methods for accessing data    stored in PostgreSQL tables (Adapted from Rdbi.PgSQL, authored    by Timothy H. Keitt)

   Currently an interface to the SNPper data resource maintained at    Childrens' Boston, which curates SNP-related data from a variety of    sources.

   A new package that works with oligonucleotide microarrays designed    to monitor or confirm the existence of splice variants. It can    extract simple splice-variant information in XML format. This is    demonstrated by the connectivity to an existing database of    putative splice variants. The package can also integrate easily    with the results obtained from the package 'matchprobes'.

   Two new functions were added 'sagmbSimulateData' and 'sagmbAssess'    to quantitatively verify finite sample properties and outlier    robustness of the parameter estimation in vsn().

The released packages include tools which facilitate:

There are currently a total of 48 packages, not including precomputed annotation data packages for Affymetrix GeneChips(tm), KEGG, GO, and LocusLink mappings.

The packages and more details may be found on the Bioconductor WWW site:


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Please use that list to discuss Bioconductor specific issues, bugs, and problems. Note that every package has a vignette (a literate program which provides an annotated example of the package's use) as well as possibly some "HOWTO"s. These document the tool's usage, and are provided in the "doc" subdirectory of each package library.

For the Bioconductor development team:

Douglas Bates, University of Wisconsin, USA. Ben Bolstad, Division of Biostatistics, UC Berkeley, USA. Vince Carey, Harvard Medical School, USA. Marcel Dettling, Federal Inst. Technology, Switzerland. Sandrine Dudoit, Division of Biostatistics, UC Berkeley, USA. Byron Ellis, Harvard Department of Statistics, USA. Laurent Gautier, Technial University of Denmark, Denmark. Robert Gentleman, Harvard Medical School, USA. Jeff Gentry, Dana-Farber Cancer Institute, USA. Kurt Hornik, Technische Universitat Wien, Austria. Torsten Hothorn, Institut fuer Medizininformatik,

        Biometrie und Epidemiologie, Germany. Wolfgang Huber, DKFZ Heidelberg, Molecular Genome Analysis, Germany. Stefano Iacus, Italy
Rafael Irizarry, Department of Biostatistics (JHU), USA. Friedrich Leisch, Technische Universitat Wien, Austria. Martin Maechler, Federal Inst. Technology, Switzerland. Colin Smith, Scripps Research Institute, USA. Gordon Smyth, Walter and Eliza Hall Institute, Australia. Anthony Rossini, University of Washington

        and the Fred Hutchinson Cancer Research Center, USA. Gunther Sawitzki, Institute fur Angewandte Mathematik, Germany. Luke Tierney, University of Iowa, USA.
Jean Yee Hwa Yang, University of California, San Francisco, USA. Jianhua (John) Zhang, Dana-Farber Cancer Institute, USA.

rossini_at_u.washington.edu            http://www.analytics.washington.edu/ 
Biomedical and Health Informatics   University of Washington
Biostatistics, SCHARP/HVTN          Fred Hutchinson Cancer Research Center
UW (Tu/Th/F): 206-616-7630 FAX=206-543-3461 | Voicemail is unreliable
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