[Bioc-sig-seq] Bioconductor 2.8 is released

Fri Apr 15 19:02:40 CEST 2011

Hi João,

Your suggestion works as advertised. Just to keep it handy on the
record, this is an example

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

chooseBioCmirror("http://watson.nci.nih.gov/bioc_mirror")

biocLite("BSgenome.Hsapiens.UCSC.hg19")

Thank you,

Ivan

On Fri, Apr 15, 2011 at 12:18 PM, João Moura <palerma at gmail.com> wrote:
> Hi Ivan,
> Just look at the output of the source()
>> source("http://bioconductor.org/biocLite.R")
> BioC_mirror = http://bioconductor.org
> Change using chooseBioCmirror().
> Cheers
> On Fri, Apr 15, 2011 at 5:41 PM, Ivan Gregoretti <ivangreg at gmail.com> wrote:
>>
>> 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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>
>
>
> --
> João Moura
>