[Bioc-sig-seq] Bioconductor 2.8 is released

[Ivan Gregoretti]

Hello Dan,

Updating Bioconductor devel packages as instructed in

http://bioconductor.org/install/

usually leads to stalled downloads when it retrieves large packages.
The BSgenome packages are notorious for this.

Can you or anybody recommend a solution that does not involve manually
downloading the tar balls one by one? (Perhaps the is a mirror for
devel.)

Thank you,

Ivan



On Thu, Apr 14, 2011 at 5:33 PM, Dan Tenenbaum <dtenenba at fhcrc.org> wrote:
> Bioconductors:
>
> We are pleased to announce Bioconductor 2.8, consisting of 466
> software packages and more than 500 up-to-date annotation packages.
> There are 48 new software packages, and many updates and improvements
> to existing packages. Two software packages that were in the previous
> version have been removed. Bioconductor 2.8 is compatible with
> R 2.13.0, and is supported on Linux, 32- and 64-bit Windows, and Mac
> OS.  Visit
>
> http://bioconductor.org
>
> for details and downloads.
>
> Contents
> ========
>
> * Getting Started with Bioconductor 2.8
> * New Software Packages
> * Using Bioconductor in the cloud
>
> Getting Started with Bioconductor 2.8
> =====================================
>
> To install Bioconductor 2.8:
>
> 1. Install R 2.13.0.  Bioconductor 2.8 has been designed expressly for
> this version of R.
>
> 2. Follow the instructions here:
>
> http://bioconductor.org/install/
>
> Please visit http://bioconductor.org for details and downloads.
>
> New Software Packages
> =====================
>
> There are 48 new packages in this release of Bioconductor.
>
> a4
>
>  Automated Affymetrix Array Analysis Umbrella Package
>
> a4Base
>
>  Automated Affymetrix Array Analysis Base Package
>
> a4Classif
>
>  Automated Affymetrix Array Analysis Classification Package
>
> a4Core
>
>  Automated Affymetrix Array Analysis Core Package
>
> a4Preproc
>
>  Automated Affymetrix Array Analysis Preprocessing Package
>
> a4Reporting
>
>  Automated Affymetrix Array Analysis Reporting Package
>
> AnnotationFuncs
>
>  Annotation translation functions
>
> anota
>
>  ANalysis Of Translational Activity
>
> chopsticks
>
>  The snp.matrix and X.snp.matrix classes
>
> Clonality
>
>  Clonality testing
>
> clst
>
>  Classification by local similarity threshold
>
> clstutils
>
>  Tools for performing taxonomic assignment
>
> clusterProfiler
>
>  statistical analysis and visulization of
>  functional profiles for genes and gene clusters
>
> cn.farms
>
>  Factor Analysis for copy number estimation
>
> ENVISIONQuery
>
>  Retrieval from the ENVISION bioinformatics data portal into R
>
> ExiMiR
>
>  R functions for the normalization of Exiqon miRNA array data
>
> flowPhyto
>
>  Methods for Continuous Flow Cytometry
>
> flowPlots
>
>  analysis plots and data class for gated flow cytometry data
>
> gaia
>
>  An R package for genomic analysis of significant
>  chromosomal aberrations
>
> genefu
>
>  Relevant Functions for Gene Expression Analysis,
>  Especially in Breast Cancer
>
> genoset
>
>  Provides classes similar to ExpressionSet for copy number analysis
>
> GSVA
>
>  Gene Set Variation Analysis
>
> ibh
>
>  Interaction Based Homogeneity for Evaluating Gene Lists
>
> inveRsion
>
>  Inversions in genotype data
>
> IPPD
>
>  Isotopic peak pattern deconvolution for Protein Mass
>  Spectrometry by template matching
>
> joda
>
>  JODA algorithm for quantifying gene deregulation using knowledge
>
> lol
>
>  Lots Of Lasso
>
> mcaGUI
>
>  Microbial Community Analysis GUI
>
> mgsa
>
>  Model-based gene set analysis
>
> MLP
>
>  Mean Log P Analysis
>
> mosaics
>
>  MOdel-based one and two Sample Analysis and Inference for ChIP-Seq
>
> MSnbase
>
>  Base Functions and Classes for MS-based Proteomics
>
> NCIgraph
>
>  Pathways from the NCI Pathways Database
>
> phenoDist
>
>  Phenotypic distance measures
>
> phenoTest
>
>  Tools to test correlation between gene expression and phenotype
>
> procoil
>
>  Prediction of Oligomerization of Coiled Coil Proteins
>
> pvac
>
>  PCA-based gene filtering for Affymetrix arrays
>
> qrqc
>
>  Quick Read Quality Control
>
> RNAinteract
>
>  Estimate Pairwise Interactions from multidimensional features
>
> Rsubread
>
>  a super fast, sensitive and accurate read aligner for mapping
>  next-generation sequencing reads
>
> seqbias
>
>  Estimation of per-position bias in high-throughput sequencing data
>
> snm
>
>  Supervised Normalization of Microarrays
>
> snpStats
>
>  SnpMatrix and XSnpMatrix classes and methods
>
> survcomp
>
>  Performance Assessment and Comparison for Survival Analysis
>
> TDARACNE
>
>  Network reverse engineering from time course data
>
> TEQC
>
>  Quality control for target capture experiments
>
> TurboNorm
>
>  A fast scatterplot smoother suitable for microarray normalization
>
> Vega
>
>  An R package for copy number data segmentation
>
>
> Using Bioconductor in the cloud
> ===============================
>
> This release features the Bioconductor Amazon Machine
> Image (AMI), which allows easy access to R and Bioconductor
> within the Elastic Compute Cloud (EC2). It's easy to run
> parallelizable tasks on MPI clusters, run R from within
> your web browser using RStudio Server, and more. No
> installation required. Information available at:
>
> http://bioconductor.org/help/bioconductor-cloud-ami/
>
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