[Bioc-sig-seq] Bioconductor 2.8 is released

Ivan Gregoretti ivangreg at gmail.com
Fri Apr 15 17:41:36 CEST 2011


Great.

Would you mind showing how you can update the packages using any of
those mirrors?

Thank you,

Ivan



On Fri, Apr 15, 2011 at 11:34 AM, Dan Tenenbaum <dtenenba at fhcrc.org> wrote:
> On Fri, Apr 15, 2011 at 8:10 AM, Ivan Gregoretti <ivangreg at gmail.com> wrote:
>> 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.)
>
> Hi Ivan,
>
> There are mirrors for release and devel here:
>
> http://bioconductor.org/about/mirrors/
>
> Dan
>
>
>>
>> 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/
>>>
>>> _______________________________________________
>>> Bioc-sig-sequencing mailing list
>>> Bioc-sig-sequencing at r-project.org
>>> https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing
>>>
>>
>



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