[BioC] Bioconductor 2.3 Mac OS X 10.4 and 10.5 binary packages are available

[Patrick Aboyoun]

For the first time ever, Bioconductor is available on both Mac OS X 10.4 
(Tiger) and Mac OS X 10.5 (Leopard). These packages can be downloaded 
using biocLite in the standard fashion. For example to obtain the 
Biobase package from within R:

    source("http://bioconductor.org/biocLite.R")
    biocLite("Biobase")

You can also access these packages from the bioconductor website, where 
package downloads are now supplied in four forms:  source package, 
Windows binary package, Mac OS X 10.4 (Tiger) binary package, and Mac OS 
X 10.5 (Leopard) binary package.

http://bioconductor.org/packages/release/bioc/html/Biobase.html

Some of these binary packages assume you have made additional 
installations, like Graphviz, on your machine. For more information on 
these additional installations see "R for Mac OS X Developer's Page" at 
http://r.research.att.com.


Patrick



Patrick Aboyoun wrote:
> Bioconductors:
>
> We are pleased to announce the release of Bioconductor 2.3. This 
> release includes 36 new software packages, and many changes to 
> existing packages. Bioconductor 2.3 is comprised of 294 software 
> packages and is compatible with the recently released R 2.8.0.
>
> Please visit http://bioconductor.org for details and downloads.
>
>
> IMPORTANT NOTE FOR MAC USERS:  R 2.8.0 is using a new Mac OS X binary 
> package distribution system and the CRAN and BioC repositories need to 
> catch up with this change. If you are using Mac OS X, please refrain 
> from migrating to R-2.8.0 until these new binary package repositories 
> are put in place, or use 'type="source"' when installing packages 
> using biocLite.
>
>
> Contents
> ========
>
>  o Release Highlight
>  o Getting Started with Bioconductor 2.3
>  o New Software Packages
>  o Software Packages in 2.2 that didn't make it to 2.3
>
>
> Release Highlight
> =================
>
> This release contains a septet of packages (BSgenome, Biostrings, 
> ShortRead, IRanges, HilbertVis, HilbertVisGUI, and rtracklayer) that 
> are suited to analyze 'next generation' high-throughput DNA sequence 
> data. The BSgenome package provides the backbone for representing 
> genome sequences from many different organisms including human, mouse, 
> rat, dog, chimp, chicken, cow, fruit fly, honey bee, yeast, E. coli, 
> C. elegans, and arabidopsis. The Biostrings package performs fast or 
> flexible alignments between reads and genomes. The ShortRead package 
> provides tools for importation/exportation and quality assurance of 
> common data formats. The IRanges package offers an emerging 
> infrastructure for managing very large data objects and for 
> range-based data representation. The packages HilbertVis and 
> HilbertVisGUI display data with space-filling (Hilbert) curves that 
> maintain the spatial information implied by the linearity of 
> chromosomes. The rtracklayer package provides an interface to genome 
> browsers and their annotation tracks.
>
>
> Getting Started with Bioconductor 2.3
> =====================================
>
> IMPORTANT: MAC USERS: see the important note above.
>
> To install Bioconductor 2.3
>
> 1. Install R 2.8.0.  Bioconductor 2.3 has been designed expressly for 
> this version of R.
>
> 2. Follow the instructions here:
>
>   http://bioconductor.org/docs/install
>
> Please visit http://bioconductor.org for details and downloads.
>
>
> New Packages
> ============
>
> The following packages are new in this release of Bioconductor; visit
>
>  http://bioconductor.org/packages/release/Software.html
>
> for links to all package descriptions.
>
>
> affyContam
> Structured corruption of cel file data to demonstrate QA effectiveness
>
> Agi4x44PreProcess
> Preprocesses Agilent 4x44 array data
>
> ArrayExpress
> Accesses the ArrayExpress microarray database at EBI
>
> arrayMvout
> Analyzes AffyBatch instances
>
> ArrayTools
> Quality assessment and differentially gene expression detection for 
> Affymetrix GeneChips
>
> BicARE
> Biclustering Analysis and Results Exploration
>
> CGHbase
> Base functions and classes for arrayCGH data analysis
>
> CGHregions
> Dimension reduction for arrayCGH data with minimal information loss
>
> ChemmineR
> Compound Data Mining Framework
>
> CMA
> Synthesis of microarray-based classification
>
> DFP
> Supervised technique for identifying differentially expressed genes 
> using Fuzzy Patterns (FPs).
>
> domainsignatures
> Finds significantly enriched gene classifications based on their 
> InterPro domain structure
>
> dualKS
> Training and classifying gene expression data sets using a 
> Kolmogorov-Smirnov rank-sum based algorithm
>
> edgeR
> Estimates and tests for differential expression in multiple digital 
> gene expression libraries
>
> HELP
> Pipeline for analyzing HELP microarray data that includes graphical 
> and mathematical tools
>
> HilbertVis
> Functions to visualize long vectors of integer data by means of 
> Hilbert curves
>
> HilbertVisGUI
> An interactive tool to visualize long vectors of integer data by means 
> of Hilbert curves
>
> IRanges
> Infrastructure for managing large data objects and range-based data 
> representations
>
> ITALICS
> Normalizes Affymetrix GeneChip Human Mapping 100K and 500K set
>
> iterativeBMA
> Bayesian Model Averaging (BMA) of classification models of 2-class 
> microarray samples
>
> iterativeBMAsurv
> Uses Bayesian Model Averaging (BMA) of survival analysis models of 
> microarray data
>
> KCsmart
> Multi-sample aCGH analysis package using kernel convolution
>
> logitT
> Implements the Logit-t algorithm
>
> LPEadj
> Extends the LPE algorithm
>
> MEDME
> Determines absolute and relative DNA methylation scores from MeDIP 
> enrichment measurements
>
> miRNApath
> Provides pathway enrichment techniques for miRNA expression data
>
> microRNA
> Accesses different data resources for microRNAs
>
> minet
> Implements methods for inferring mutual information networks from data.
>
> multiscan
> Estimates gene expressions from several laser scans of the same 
> microarray
>
> parody
> Provides routines for univariate and multivariate outlier detection
>
> PLPE
> Performs tests for paired high-throughput data
>
> RNAither
> Analyzes cell-based RNAi screens
>
> RpsiXML
> Queries, data structure and interface to visualization of interaction 
> datasets
>
> SIM
> Finds associations between DNA copy number and gene expression
>
> ShortRead
> Representation of high-throughput, short-read sequencing data
>
> xmapbridge
> Plots graphs in the X:Map genome browser
>
>
> Software Packages in 2.2 that didn't make it to 2.3
> ===================================================
>
> 1. SemSim
> 2. widgetInvoke
>
>
>
>    Thanks to all who contributed to this release and made it a reality!
>
>
>        The Biocore Team
>
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