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/

Congratulations on the release, folks! Two things. (1) Regarding the packages: > lol > > ?Lots Of Lasso (a) This made me lol (b) then I thought to myself "I wish I thought of that name" (c) then I thought to myself "I've got to check this out" (d) then I went to the bioconductor software page to find it, and it seems MIA (e) which, I don't know why, also made me lol (Just wanted to file the bug report) Also: > 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). This is a great idea, thanks to all involved for doing this. -- Steve Lianoglou Graduate Student: Computational Systems Biology ?| Memorial Sloan-Kettering Cancer Center ?| Weill Medical College of Cornell University Contact Info: http://cbio.mskcc.org/~lianos/contact

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/ > > _______________________________________________ > Bioc-sig-sequencing mailing list > Bioc-sig-sequencing at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing >