Sparse and Dense Matrix Classes and Methods

Douglas Bates <bates@stat.wisc.edu> and Martin Maechler

Classes and methods for dense and sparse matrices and
    operations on them using 'LAPACK' and 'SuiteSparse'.

methods, graphics, grid, stats, utils, lattice

not possible, since we use data/*.R *and* our classes

FastICA Algorithms to perform ICA and Projection Pursuit

J L Marchini <marchini@stats.ox.ac.uk>, C Heaton
        <chrisheaton99@yahoo.com> and B D Ripley
        <ripley@stats.ox.ac.uk>

Implementation of FastICA algorithm to perform Independent
        Component Analysis (ICA) and Projection Pursuit.

Biobase: Base functions for Bioconductor

R. Gentleman, V. Carey, M. Morgan, S. Falcon

Functions that are needed by many other packages or which
        replace R functions.

tools, tkWidgets, ALL, RUnit, golubEsets

tools.R strings.R environment.R vignettes.R packages.R
AllGenerics.R VersionsClass.R VersionedClasses.R
methods-VersionsNull.R methods-VersionedClass.R DataClasses.R
methods-aggregator.R methods-container.R methods-MIAxE.R
methods-MIAME.R methods-AssayData.R
methods-AnnotatedDataFrame.R methods-eSet.R
methods-ExpressionSet.R methods-MultiSet.R methods-SnpSet.R
methods-NChannelSet.R anyMissing.R rowOp-methods.R
updateObjectTo.R methods-ScalarObject.R zzz.R

Interface to BioMart databases (e.g. Ensembl, COSMIC ,Wormbase
and Gramene)

Steffen Durinck <biomartdev@gmail.com>, Wolfgang Huber

Sean Davis <sdavis2@mail.nih.gov>, Francois Pepin, Vince
S. Buffalo

In recent years a wealth of biological data has become available in public data repositories. Easy access to these valuable data resources and firm integration with data analysis is needed for comprehensive bioinformatics data analysis.  biomaRt provides an interface to a growing collection of databases implementing the BioMart software suite (http://www.biomart.org). The package enables retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas or write complex SQL queries. Examples of BioMart databases are Ensembl, COSMIC, Uniprot, HGNC, Gramene, Wormbase and dbSNP mapped to Ensembl. These major databases give biomaRt users direct access to a diverse set of data and enable a wide range of powerful online queries from gene annotation to database mining.