Bioconductor 2.3 is released
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Patrick Aboyoun ★ 1.6k
@patrick-aboyoun-6734
Last seen 9.5 years ago
United States
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
aCGH Sequencing miRNA Microarray Visualization Bayesian Classification Survival Yeast LPE • 1.5k views
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Patrick Aboyoun ★ 1.6k
@patrick-aboyoun-6734
Last seen 9.5 years ago
United States
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 > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor
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Hi, On Oct 29, 2008, at 4:32 PM, Patrick Aboyoun wrote: > 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. That's great! Out of curiosity, is there anything we have to keep in mind with 32 vs 64bit setups (since some packages have compiled c code(?))? Thanks, -steve -- Steve Lianoglou Graduate Student: Physiology, Biophysics and Systems Biology Weill Medical College of Cornell University http://cbio.mskcc.org/~lianos
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Steve, All packages that are posted for the Mac OS X 10.5 support execution in i386 (32-bit), ppc (32-bit), and x86_64 (64-bit) modes. Patrick Steve Lianoglou wrote: > Hi, > > On Oct 29, 2008, at 4:32 PM, Patrick Aboyoun wrote: > >> 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. > > > That's great! > > Out of curiosity, is there anything we have to keep in mind with 32 vs > 64bit setups (since some packages have compiled c code(?))? > > Thanks, > -steve > > -- > Steve Lianoglou > Graduate Student: Physiology, Biophysics and Systems Biology > Weill Medical College of Cornell University > > http://cbio.mskcc.org/~lianos > > > >
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