http://www.bioconductor.org/ New Bioconductor Packages (devel branch) en-us ruby Sat, 1 Jan 2012 00:00:00 GMTDavide RambaldiThis package estimate the proliferation of a cell population in cell-tracking dye studies. The package uses an R implementation of the Levenberg-Marquardt algorithm (minpack.lm) to fit a set of peaks (corresponding to different generations of cells) over the proliferation-tracking dye distribution in a FACS experiment. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/flowFit.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTCharles Plessy <plessy@riken.jp>Identify and analyse B and T cell receptors at a high throughput. The genes encoding T cell receptors and B cell receptors (the antibodies) are created by somatic recombination, generating an immense combination of V, (D) and J segments. Additional processes during the recombination create extra sequence diversity between the V an J segments. Collectively, this hyper-variable region is called the CDR3 loop. . The purpose of this package is to process and quantitatively analyse millions of V-CDR3-J combination, called clonotypes, from multiple libraries. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/clonotypeR.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTH. Pages and P. AboyounMemory efficient S4 classes for storing sequences "externally" (behind an R external pointer, or on disk). <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/XVector.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTDanni Yu <dyu@purdue.edu>, Wolfgang Huber <whuber@embl.de> and Olga Vitek <ovitek@purdue.edu>The purpose of this package is to discover the genes that are differentially expressed between two conditions in RNA-seq experiments. Gene expression is measured in counts of transcripts and modeled with the Negative Binomial (NB) distribution using a shrinkage approach for dispersion estimation. The method of moment (MM) estimates for dispersion are shrunk towards an estimated target, which minimizes the average squared difference between the shrinkage estimates and the initial estimates. The exact per-gene probability under the NB model is calculated, and used to test the hypothesis that the expected expression of a gene in two conditions identically follow a NB distribution. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/sSeq.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTD. Bindreither, M. Carlson, M. Morgan, H. PagesThis package allows the user to create, manipulate, and visualize splicing graphs and their bubbles based on a gene model for a given organism. Additionally it allows the user to assign RNA-seq reads to the edges of a set of splicing graphs, and to summarize them. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/SplicingGraphs.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTKatja Hebestreit, Hans-Ulrich KleinThe BiSeq package provides useful classes and functions to handle and analyze targeted bisulfite sequencing (BS) data such as reduced-representation bisulfite sequencing (RRBS) data. In particular, it implements an algorithm to detect differentially methylated regions (DMRs). The package takes already aligned BS data from one or multiple samples. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/BiSeq.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTJiri Hon, Matej Lexa, Tomas Martinek and Kamil Rajdl with contributions from Daniel KopecekThis package provides functions for identification and visualization of potential intramolecular triplex patterns in DNA sequence. The main functionality is to detect the positions of subsequences capable of folding into an intramolecular triplex (H-DNA) in a much larger sequence. The potential H-DNA (triplexes) should be made of as many cannonical nucleotide triplets as possible. The package includes visualization showing the exact base-pairing in 1D, 2D or 3D. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/triplex.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTKarolis Uziela and Antti HonkelaThe prebs package aims at making RNA-sequencing (RNA-seq) data more comparable to microarray data. The comparability is achieved by summarizing sequencing-based expressions of probe regions using a modified version of RMA algorithm. The pipeline takes mapped reads in BAM format as an input and produces either gene expressions or original microarray probe set expressions as an output. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/prebs.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTLeif Varemo <piano.rpkg@gmail.com> and Intawat Nookaew <piano.rpkg@gmail.com>Piano performs gene set analysis using various statistical methods, from different gene level statistics and a wide range of gene-set collections. Furthermore, the Piano package contains functions for combining the results of multiple runs of gene set analyses. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/piano.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTGabriele SchweikertThis package detects statistically significant difference between read enrichment profiles in different ChIP-Seq samples. To take advantage of shape differences it uses Kernel methods (Maximum Mean Discrepancy, MMD). <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/MMDiff.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTJoshua GouldInteractive exploration of matrices in GENE-E. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/GENE.E.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTRaphael AggioThe Pathway Activity Profiling - PAPi - is an R package for predicting the activity of metabolic pathways based solely on a metabolomics data set containing a list of metabolites identified and their respective abundances in different biological samples. PAPi generates hypothesis that improves the final biological interpretation. See Aggio, R.B.M; Ruggiero, K. and Villas-Boas, S.G. (2010) - Pathway Activity Profiling (PAPi): from metabolite profile to metabolic pathway activity. Bioinformatics. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/PAPi.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTHector Corrada Bravo, Rafael A. Irizarry and Jeffrey T. LeekImplements gene expression anti-profiles as described in Corrada Bravo et al., BMC Bioinformatics 2012, 13:272 doi:10.1186/1471-2105-13-272. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/antiProfiles.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTGro Nilsen, Knut Liestoel and Ole Christian Lingjaerde.Penalized least squares regression is applied to fit piecewise constant curves to copy number data to locate genomic regions of constant copy number. Procedures are available for individual segmentation of each sample, joint segmentation of several samples and joint segmentation of the two data tracks from SNP-arrays. Several plotting functions are available for visualization of the data and the segmentation results. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/copynumber.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTSara Aibar, Celia Fontanillo and Javier De Las Rivas. Bioinformatics and Functional Genomics Group. Cancer Research Center (CiC-IBMCC, CSIC/USAL). Salamanca. Spain.Comprehensive package to automatically train a multi-class SVM classifier based on gene expression data. Provides transparent selection of gene markers, their coexpression networks, and an interface to query the classifier. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/geNetClassifier.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTXi Wang <Xi.Wang@newcastle.edu.au>The package generally provides methods for gene set enrichment analysis of high-throughput RNA-Seq data by integrating differential expression and splicing. It uses negative binomial distribution to model read count data, which accounts for sequencing biases and biological variation. Based on permutation tests, statistical significance can also be achieved regarding each gene's differential expression and splicing, respectively. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/SeqGSEA.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTOscar Flores, Anna MantsokiR package for programmatic retrieval of information from DAS servers <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/DASiR.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTJoseph Nathaniel Paulson, Mihai Pop, Hector Corrada BravometagenomeSeq is designed to determine features (be it Operational Taxanomic Unit (OTU), species, etc.) that are differentially abundant between two or more groups of multiple samples. metagenomeSeq is designed to address the effects of both normalization and under-sampling of microbial communities on disease association detection and the testing of feature correlations. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/metagenomeSeq.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTMarc CarlsonA client for retrieving data from the Bioconductor AnnotationHub online services. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/AnnotationHub.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTCalin Voichita <calin@wayne.edu> and Sorin Draghici <sorin@wayne.edu>Suite of tools for functional analysis <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/ROntoTools.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTKevin HoranThe eiR package provides utilities for accelerated structure similarity searching of very large small molecule data sets using an embedding and indexing approach. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/eiR.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTF.EduatiThis package integrates literature-constrained and data-driven methods to infer signalling networks from perturbation experiments. It permits to extends a given network with links derived from the data via various inference methods, and uses information on physical interactions of proteins to guide and validate the integration of links. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/CNORfeeder.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTAdrian AlexaA rich R interface to Illumina's BaseSpace cloud computing environment, enabling the fast development of data analysis and visualisation tools. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/BaseSpaceR.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTXinyi YANG Developer, Jennifer E. DENT Developer and Christine NARDINI SupervisorThis package can optimize the parameter in S-system models given time series data <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/SPEM.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTXiuwen ZhengBig data management of genome-wide variants using the CoreArray library, where genotypic data and annotations are stored in an array-oriented manner, offering efficient access of genetic variants using the R language. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/SeqArray.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTRNA-seq, sample size <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/RNASeqPower.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTWeijun LuoPathview is a tool set for pathway based data integration and visualization. It maps and renders a wide variety of biological data on relevant pathway graphs. All users need is to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps user data to the pathway, and render pathway graph with the mapped data. In addition, Pathview also seamlessly integrates with pathway and gene set analysis tools for large-scale and fully automated analysis. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/pathview.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTXin Zengjmosaics detects enriched regions of ChIP-seq data sets jointly. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/jmosaics.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTAskar ObulkasimDecompose given hierarchical clustering tree into non-overlapping clusters in a semi-supervised way by using available patients follow-up information as guidance. Contains functions for snipping HC tree, various cluster quality evaluation criteria, assigning new patients to one of the two given HC trees, testing the significance of clusters with permutation argument and clusters visualization using sample's molecular entropy. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/HCsnip.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTHans-Ulrich Klein, Martin SchaeferA package for the integrative analysis of microarray based gene expression and histone modification data obtained by ChIP-seq. The package provides methods for data preprocessing and matching as well as methods for fitting bayesian mixture models in order to detect genes with differences in both data types. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/epigenomix.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTGuenter KlambauerDEXUS identifies differentially expressed genes in RNA-Seq data under all possible study designs such as studies without replicates, without sample groups, and with unknown conditions. DEXUS works also for known conditions, for example for RNA-Seq data with two or multiple conditions. RNA-Seq read count data can be provided both by the S4 class Count Data Set and by read count matrices. Differentially expressed transcripts can be visualized by heatmaps, in which unknown conditions, replicates, and samples groups are also indicated. This software is fast since the core algorithm is written in C. For very large data sets, a parallel version of DEXUS is provided in this package. DEXUS is a statistical model that is selected in a Bayesian framework by an EM algorithm. DEXUS does not need replicates to detect differentially expressed transcripts, since the replicates (or conditions) are estimated by the EM method for each transcript. The method provides an informative/non-informative value to extract differentially expressed transcripts at a desired significance level or power. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/dexus.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTDiana Low, Efthymios MotakisIdentifying distinct subpopulations through multiscale time series analysis <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/deltaGseg.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTJean-Philippe Fortin, Celia M.T. Greenwood, Aurelie Labbe.Perform the Adaptive Robust Regression method (ARRm) for the normalization of methylation data from the Illumina Infinium HumanMethylation 450k assay. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/ARRmNormalization.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTThomas SandmannThe gCMAPWeb R package provides a graphical user interface for the gCMAP package. gCMAPWeb uses the Rook package and can be used either on a local machine, leveraging R's internal web server, or run on a dedicated rApache web server installation. gCMAPWeb allows users to search their own data sources and instructions to generate reference datasets from public repositories are included with the package. The package supports three common types of analyses, specifically queries with 1. one or two sets of query gene identifiers, whose members are expected to show changes in gene expression in a consistent direction. For example, an up-regulated gene set might contain genes activated by a transcription factor, a down-regulated geneset targets repressed by the same factor. 2. a single set of query gene identifiers, whose members are expected to show divergent differential expression (non-directional query). For example, members of a particular signaling pathway, some of which may be up- some down-regulated in response to a stimulus. 3. a query with the complete results of a differential expression profiling experiment. For example, gene identifiers and z-scores from a previous perturbation experiment. gCMAPWeb accepts three types of identifiers: EntreIds, gene Symbols and microarray probe ids and can be configured to work with any species supported by Bioconductor. For each query submission, significantly similar reference datasets will be identified and reported in graphical and tabular form. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/gCMAPWeb.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTAlex Cornish and Florian MarkowetzThis package provides methods for measuring the strength of association between a network and a phenotype. It does this by measuring clustering of the phenotype across the network. Vertices can also be individually ranked by their strength of association with high-weight vertices. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/SANTA.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTJulian GehringSignificance assessment for distance measures of time-course protein profiles <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/proteinProfiles.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTMichael Love (MPIMG Berlin), Simon Anders, Wolfgang Huber (EMBL Heidelberg)Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/DESeq2.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTRaffaele A Calogero, Matteo Carrara, Marco Beccuti, Francesca CorderoThis package facilitates the characterisation of fusion products events. It allows to import fusion data results from the following fusion finders: bellerophontes, deFuse, FusionFinder, FusionHunter, mapSplice, tophat-fusion, FusionMap, STAR. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/chimera.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTVanja Haberle, Department of Biology, University of Bergen, Norway <vanja.haberle@bio.uib.no>Preprocessing of CAGE sequencing data, identification and normalization of transcription start sites and downstream analysis of transcription start sites clusters (promoters). <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/CAGEr.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTYang DuIn this package, a Hidden Semi Markov Model (HSMM) and one homogeneous segmentation model are designed and implemented for segmentation genomic data, with the aim of assisting in transcripts detection using high throughput technology like RNA-seq or tiling array, and copy number analysis using aCGH or sequencing. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/biomvRCNS.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTLikun Wang <wanglk@hsc.pku.edu.cn>cisPath is an R package for identification and visualization of the shortest functional paths between proteins in the protein-protein interaction network. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/cisPath.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTAnne BitonThe goal of MineICA is to make easier the interpretation of the interpretation of a decomposition obtained by Independent Component Analysis on transcriptomic data. It helps the biological interpretation of the components by studying their association with variables (e.g sample annotations) and gene sets, and enables the comparison of components from different datasets using correlation-based graph. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/MineICA.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTBettina Knapp, Johanna Mazur, Lars KaderalilpNet takes perturbation data as input and generates an LP model which allows the inference of signaling networks. For parameter identification either leave-one-out cross-validation or stratified n-fold cross-validation can be used. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/lpNet.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTMengjie Chen <mengjie.chen@yale.edu>, Hongyu Zhao <hongyu.zhao@yale.edu>SomatiCA is a software suite that is capable of identifying, characterizing, and quantifying somatic CNAs from cancer genome sequencing. First, it uses read depths and lesser allele frequencies (LAF) from mapped short sequence reads to segment the genome and identify candidate CNAs. Second, SomatiCA estimates the admixture rate from the relative copy-number profile of tumor-normal pair by a Bayesian finite mixture model. Third, SomatiCA quantifies absolute somatic copy-number and subclonality for each genomic segment to guide its characterization. Results from SomatiCA can be further integrated with single nucleotide variations (SNVs) to get a better understanding of the tumor evolution. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/SomatiCA.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTFrank KramerParses BioPAX files and represents them in R, at the moment BioPAX level 2 and level 3 are supported. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/rBiopaxParser.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTAndrea Rau, Melina Gallopin, Gilles Celeux, and Florence JaffrezicThis package implements a filtering procedure for replicated transcriptome sequencing data based on a global Jaccard similarity index in order to identify genes with low, constant levels of expression across one or more experimental conditions. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/HTSFilter.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTLukas Burger, Dimos Gaidatzis, Dirk Schubeler and Michael StadlerThis is a package for the discovery of regulatory regions from Bis-seq data <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/MethylSeekR.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTC. PaciniThis package generates ranked lists of differential gene expression for either disease or drug profiles. Input data can be downloaded from Array Express or GEO, or from local CEL files. Ranked lists of differential expression and associated p-values are calculated using Limma. Enrichment scores (Subramanian et al. PNAS 2005) are calculated to a reference set of default drug or disease profiles, or a set of custom data supplied by the user. Network visualisation of significant scores are output in Cytoscape format. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/DrugVsDisease.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTBhaskar Dutta <bhaskar.dutta@gmail.com>, Anders Wallqvist <awallqvist@bhsai.org>, and Jaques Reifman <jreifman@bhsai.org>PathNet uses topological information present in pathways and differential expression levels of genes (obtained from microarray experiment) to identify pathways that are 1) significantly enriched and 2) associated with each other in the context of differential expression. The algorithm is described in: PathNet: A tool for pathway analysis using topological information. Dutta B, Wallqvist A, and Reifman J. Source Code for Biology and Medicine 2012 Sep 24;7(1):10. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/PathNet.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTPaolo Martini <paolo.cavei@gmail.com>, Gabriele Sales <gabriele.sales@unipd.it>, Chiara Romualdi <chiara.romualdi@unipd.it>clipper is a package for topological gene set analysis. It implements a two-step empirical approach based on the exploitation of graph decomposition into a junction tree to reconstruct the most relevant signal path. In the first step clipper selects significant pathways according to statistical tests on the means and the concentration matrices of the graphs derived from pathway topologies. Then, it "clips" the whole pathway identifying the signal paths having the greatest association with a specific phenotype. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/clipper.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTDavid Rossell, Camille Stephan-Otto, Manuel KroissInfer alternative splicing from paired-end RNA-seq data. The model is based on counting paths across exons, rather than pairwise exon connections, and estimates the fragment size and start distributions non-parametrically, which improves estimation precision. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/casper.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTDan TenenbaumA package that provides a client interface to the KEGG REST server. Based on KEGGSOAP by J. Zhang, R. Gentleman, and Marc Carlson, and KEGG (python package) by Aurelien Mazurie. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/KEGGREST.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTAnita Lerch, Dimos Gaiditzis and Michael StadlerThis package provides a framework for the quantification and analysis of Short Reads. It covers a complete workflow starting from raw sequence reads, over creation of alignments and quality control plots, to the quantification of genomic regions of interest. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/QuasR.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTFlorian Hahne, Anita Lerch, Michael B StadlerThis package provides an R wrapper around the popular bowtie short read aligner and around SpliceMap, a de novo splice junction discovery and alignment tool. The package is used by the QuasR bioconductor package. We recommend to use the QuasR package instead of using Rbowtie directly. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/Rbowtie.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTFrederic Fournier <frederic.fournier@crchuq.ulaval.ca>, Charles Joly Beauparlant <charles.joly-beauparlant@crchul.ulaval.ca>, Rene Paradis <rene.paradis@genome.ulaval.ca>, Arnaud Droit <arnaud.droit@crchuq.ulaval.ca>This package encapsulate X!Tandem in R. In its most basic functionality, this package allows to call tandem(input) from R, just as tandem.exe /path/to/input.xml would be used to run X!Tandem from the command line. Classes are also provided for taxonomy and parameters objects and methods are provided to convert xml files to R objects and vice versa. This package is the first step in an attempt to provide a reliable worflow for proteomics analysis in R. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/rTANDEM.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTChristoph BartenhagenRSVSim is a package for the simulation of deletions, insertions, inversion, tandem-duplications and translocations of various sizes in any genome available as FASTA-file or BSgenome data package. SV breakpoints can be placed uniformly accross the whole genome, with a bias towards repeat regions and regions of high homology (for hg19) or at user-supplied coordinates. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/RSVSim.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTMarie-Pier Scott-Boyer and Greg Imholteintegrated Bayesian Modeling of eQTL data <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/iBMQ.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTGregory Ryslik, Hongyu ZhaoIdentifies mutational clusters of amino acids in a protein while utilizing the proteins tertiary structure via a graph theoretical model. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/GraphPAC.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTValerie Obenchain <vobencha@fhcrc.org>,Query the Ensembl Variant Effect Predictor via the perl API <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/ensemblVEP.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTLeonard C Schalkwyk, Ruth Pidsley, Chloe CY Wong, with functions contributed by Nizar Touleimat, Matthieu Defrance, Andrew Teschendorff, Jovana Maksimovic15 flavours of betas and three performance metrics, with methods for objects produced by methylumi, minfi and IMA packages. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/wateRmelon.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTRafael A. Irizarry, Martin Aryee, Hector Corrada Bravo, Kasper D. Hansen, Harris A. JaffeeTools for finding bumps in genomic data <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/bumphunter.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTAli Bashashati, Reza Haffari, Jiarui Ding, Gavin Ha, Kenneth Liu, Jamie Rosner and Sohrab ShahDriverNet is a package to predict functional important driver genes in cancer by integrating genome data (mutation and copy number variation data) and transcriptome data (gene expression data). The different kinds of data are combined by an influence graph, which is a gene-gene interaction network deduced from pathway data. A greedy algorithm is used to find the possible driver genes, which may mutated in a larger number of patients and these mutations will push the gene expression values of the connected genes to some extreme values. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/DriverNet.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTLaurent Gatto and Lisa M. Breckels with contributions from Thomas Burger and Samuel WieczorekThis package implements pattern recognition techniques on quantitiative mass spectrometry data to infer protein sub-cellular localisation. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/pRoloc.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTPierre Bushel <bushel@niehs.nih.gov>This package contains the function to assess the batch sourcs by fitting all "sources" as random effects including two-way interaction terms in the Mixed Model(depends on lme4 package) to selected principal components, which were obtained from the original data correlation matrix. This package accompanies the book "Batch Effects and Noise in Microarray Experiements, chapter 12. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/pvca.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTMartin MorganThis package provides modified versions and novel implementation of functions for parallel evaluation, tailored to use with Bioconductor objects. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/BiocParallel.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTGwenael G.R. LedayThe present package implements a flexible framework for modeling the relationship between DNA copy number and gene expression data using Piecewise Linear Regression Splines (PLRS). <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/plrs.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTMarc CarlsonA collection of functions for retrieving, processing and repackaging the Uniprot web services. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/UniProt.ws.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTDavid Venet <davenet@ulb.ac.be>Signal-to-Noise applied to Gene Expression Experiments. Signal-to-noise ratios can be used as a proxy for quality of gene expression studies and samples. The SNRs can be calculated on any gene expression data set as long as gene IDs are available, no access to the raw data files is necessary. This allows to flag problematic studies and samples in any public data set. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/SNAGEE.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTKeith Baggerly, Henrik Bengtsson, Kasper Daniel Hansen, Matt RitchieTools for parsing Illumina's microarray output files, including IDAT. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/illuminaio.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTYue LiInfer and discriminate RIP peaks from RIP-seq alignments using two-state HMM with negative binomial emission probability. While RIPSeeker is specifically tailored for RIP-seq data analysis, it also provides a suite of bioinformatics tools integrated within this self-contained software package comprehensively addressing issues ranging from post-alignments processing to visualization and annotation. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/RIPSeeker.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTLuigi Marchionni <marchion@jhu.edu>, Anuj Gupta <Anuj Gupta <agupta52@jhu.edu>The matchBox package enables comparing ranked vectors of features, merging multiple datasets, removing redundant features, using CAT-plots and Venn diagrams, and computing statistical significance. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/matchBox.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTMatt Settles <msettles@uidaho.edu>, Sam Hunter, Brice Sarver, Ilia Zhbannikov, Kyu-Chul ChorSFFreader reads sequence, qualities and clip point values from sff files generated by Roche 454 and Life Sciences Ion Torrent sequencers. The plan is to also write out sff files and to read in flowgrams with some utils <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/rSFFreader.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTOscar Reina, David RossellWe provide intuitive maps to visualize the association between genetic elements, with emphasis on epigenetics. The approach is based on Multi-Dimensional Scaling. We provide several sensible distance metrics, and adjustment procedures to remove systematic biases typically observed when merging data obtained under different technologies or genetic backgrounds. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/chroGPS.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTSonia Tarazona, Pedro Furio-Tari, Alberto Ferrer and Ana ConesaAnalysis of RNA-seq expression data or other similar kind of data. Exploratory plots to evualuate saturation, count distribution, expression per chromosome, type of detected features, features length, etc. Differential expression between two experimental conditions with no parametric assumptions. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/NOISeq.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTJulius MullerThis package provides efficient tools to generate, access and display read densities of sequencing based data sets such as from RNA-Seq and ChIP-Seq. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/TransView.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTJonathan CairnsRcade (which stands for "R-based analysis of ChIP-seq And Differential Expression") is a tool for integrating ChIP-seq data with differential expression summary data, through a Bayesian framework. A key application is in identifing the genes targeted by a transcription factor of interest - that is, we collect genes that are associated with a ChIP-seq peak, and differential expression under some perturbation related to that TF. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/Rcade.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTGregoire Pau, Jens ReederLibraries to perform NGS analysis. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/HTSeqGenie.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTDaniel Lai, Gavin Ha, Sohrab ShahCorrects GC and mappability biases for readcounts (i.e. coverage) in non-overlapping windows of fixed length for single whole genome samples, yielding a rough estimate of copy number for furthur analysis. Designed for rapid correction of high coverage whole genome tumour and normal samples. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/HMMcopy.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTDavid Henriques, Thomas CokelaerODE add-on to CellNOptR <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/CNORode.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTPeter M. HavertyThis package defines a "BigMatrix" ReferenceClass which adds safety and convenience features to the filebacked.big.matrix class from the bigmemory package. BigMatrix protects against segfaults by monitoring and gracefully restoring the connection to on-disk data and it also protects against accidental data modification with a filesystem-based permissions system. We provide utilities for using BigMatrix-derived classes as assayData matrices within the Biobase package's eSet family of classes. BigMatrix provides some optimizations related to attaching to, and indexing into, file-backed matrices with dimnames. Additionally, the package provides a "BigMatrixFactor" class, a file-backed matrix with factor properties. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/bigmemoryExtras.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTA. MacNamaraThis add-on to the package CellNOptR handles time-course data, as opposed to steady state data in CellNOptR. It scales the simulation step to allow comparison and model fitting for time-course data. Future versions will optimize delays and strengths for each edge. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/CNORdt.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTBenny Chain <b.chain@ucl.ac.uk>provides a pipeline for the low-level analysis of gene expression microarray data, primarily Agilent data <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/agilp.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTStephen R. Piccolo and W. Evan JohnsonSCAN is a microarray normalization method to facilitate personalized-medicine workflows. Rather than processing microarray samples as groups, which can introduce biases and present logistical challenges, SCAN normalizes each sample individually by modeling and removing probe- and array-specific background noise using only data from within each array. SCAN can be applied to one-channel (e.g., Affymetrix) or two-channel (e.g., Agilent) microarrays. The Universal Probability of expression Codes (UPC) method is an extension of SCAN that generates probability-of-expression values. These values can be interpreted as the probability that a given genomic feature (e.g., gene, transcript) is expressed above the background in a given sample. The UPC method can be applied to one-channel or two-channel microarrays as well as to RNA-Seq read counts. Because UPC values are represented on the same scale and have an identical interpretation for each platform, they can be used for cross-platform data integration.) <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/SCAN.UPC.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTJason A. Hackney, Melanie Huntley, Jessica L. Larson, Christina Chaivorapol, Gabriel Becker, and Josh KaminkerThe ReportingTools software package enables users to easily display reports of analysis results generated from sources such as microarray and sequencing data. The package allows users to create HTML pages that may be viewed on a web browser such as Safari, or in other formats readable by programs such as Excel. Users can generate tables with sortable and filterable columns, make and display plots, and link table entries to other data sources such as NCBI or larger plots within the HTML page. Using the package, users can also produce a table of contents page to link various reports together for a particular project that can be viewed in a web browser. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/ReportingTools.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTTing Gong <tinggong@gmail.com> Joseph D. Szustakowski <joseph.szustakowski@novartis.com>DeconSeq is an R package for deconvolution of heterogeneous tissues based on mRNA-Seq data. It modeled expression levels from heterogeneous cell populations in mRNA-Seq as the weighted average of expression from different constituting cell types and predicted cell type proportions of single expression profiles. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/DeconRNASeq.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTJianhong Ou, Michael Brodsky, Scot Wolfe and Lihua Julie ZhuThe motifStack package is designed for graphic representation of multiple motifs with different similarity scores. It works with both DNA/RNA sequence motif and amino acid sequence motif. In addition, it provides the flexibility for users to customize the graphic parameters such as the font type and symbol colors. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/motifStack.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTThomas Sandmann <sandmann.thomas@gene.com>, Richard Bourgon <bourgon.richard@gene.com> and Sarah Kummerfeld <kummerfeld.sarah@gene.com>The gCMAP package provides a toolkit for comparing differential gene expression profiles through gene set enrichment analysis. Starting from normalized microarray or RNA-seq gene expression values (stored in lists of ExpressionSet and CountDataSet objects) the package performs differential expression analysis using the limma or DESeq packages. Supplying a simple list of gene identifiers, global differential expression profiles or data from complete experiments as input, users can use a unified set of several well-known gene set enrichment analysis methods to retrieve experiments with similar changes in gene expression. To take into account the directionality of gene expression changes, gCMAPQuery introduces the SignedGeneSet class, directly extending GeneSet from the GSEABase package. To increase performance of large queries, multiple gene sets are stored as sparse incidence matrices within CMAPCollection eSets. gCMAP offers implementations of 1. Fisher's exact test (Fisher, J R Stat Soc, 1922) 2. The "connectivity map" method (Lamb et al, Science, 2006) 3. Parametric and non-parametric t-statistic summaries (Jiang & Gentleman, Bioinformatics, 2007) and 4. Wilcoxon / Mann-Whitney rank sum statistics (Wilcoxon, Biometrics Bulletin, 1945) as well as wrappers for the 5. camera (Wu & Smyth, Nucleic Acid Res, 2012) 6. mroast and romer (Wu et al, Bioinformatics, 2010) functions from the limma package and 7. wraps the gsea method from the mgsa package (Bauer et al, NAR, 2010). All methods return CMAPResult objects, an S4 class inheriting from AnnotatedDataFrame, containing enrichment statistics as well as annotation data and providing simple high-level summary plots. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/gCMAP.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTAlejandra Gonzalez-Beltran, Audrey Kauffmann, Steffen Neumann, Gabriella Rustici, ISA TeamThe Investigation / Study / Assay (ISA) tab-delimited format is a general purpose framework with which to collect and communicate complex metadata (i.e. sample characteristics, technologies used, type of measurements made) from experiments employing a combination of technologies, spanning from traditional approaches to high-throughput techniques. Risa allows to access metadata/data in ISA-Tab format and build Bioconductor data structures. Currently, data generated from microarray, flow cytometry and metabolomics-based (i.e. mass spectrometry) assays are supported. The package is extendable and efforts are undergoing to support metadata associated to proteomics assays. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/Risa.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTLaurent GattoA simple interface to and data from the Human Protein Atlas project. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/hpar.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTSepp Hochreiter <hochreit@bioinf.jku.at>A package to identify very short IBD segments in large sequencing data by FABIA biclustering. Two haplotypes are identical by descent (IBD) if they share a segment that both inherited from a common ancestor. Current IBD methods reliably detect long IBD segments because many minor alleles in the segment are concordant between the two haplotypes. However, many cohort studies contain unrelated individuals which share only short IBD segments. This package provides software to identify short IBD segments in sequencing data. Knowledge of short IBD segments are relevant for phasing of genotyping data, association studies, and for population genetics, where they shed light on the evolutionary history of humans. The package supports VCF formats, is based on sparse matrix operations, and provides visualization of haplotype clusters in different formats. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/hapFabia.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTMarc Carlson, Herve Pages, Martin Morgan, Valerie ObenchainThe package enables a simple unified interface to several annotation packages each of which has its own schema by taking advantage of the fact that each of these packages implements a select methods. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/OrganismDbi.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTCristobal Fresno and Elmer A. Fernandezlinear ANOVA decomposition of Multivariate Designed Experiments implementation based on limma lmFit. Features: i)Flexible formula type interface, ii) Fast limma based implementation, iii) p-values for each estimated coefficient levels in each factor, iv) F values for factor effects and v) plotting functions for PCA and PLS. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/lmdme.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTYan Wang, Tyler Backman, Kevin Horan, Thomas GirkeThe fmcsR package introduces an efficient maximum common substructure (MCS) algorithms combined with a novel matching strategy that allows for atom and/or bond mismatches in the substructures shared among two small molecules. The resulting flexible MCSs (FMCSs) are often larger than strict MCSs, resulting in the identification of more common features in their source structures, as well as a higher sensitivity in finding compounds with weak structural similarities. The fmcsR package provides several utilities to use the FMCS algorithm for pairwise compound comparisons, structure similarity searching and clustering. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/fmcsR.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTPan Du, Richard BourgonThe methyAnalysis package aims for the DNA methylation data analysis and visualization. A new class is defined to keep the chromosome location information together with the data. The current version of the package mainly focus on analyzing the Illumina Infinium methylation array data, but most methods can be generalized to other methylation array or sequencing data. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/methyAnalysis.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTM. Morris, T. CokelaerThis package is an extension to CellNOptR. It contains additional functionality needed to simulate and train a prior knowledge network to experimental data using constrained fuzzy logic (cFL, rather than Boolean logic as is the case in CellNOptR). Additionally, this package will contain functions to use for the compilation of multiple optimization results (either Boolean or cFL). <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/CNORfuzzy.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTLe Pape SylvainThis package is based on the qBase algorithms published by Hellemans et al. in 2007. The EasyqpcR package allows you to import easily qPCR data files as described in the vignette. Thereafter, you can calculate amplification efficiencies, relative quantities and their standard errors, normalization factors based on the best reference genes choosen (using the SLqPCR package), and then the normalized relative quantities, the NRQs scaled to your control and their standard errors. This package has been created for low-throughput qPCR data analysis. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/EasyqpcR.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTJianhong Ou and Lihua Julie ZhuAppliation for discovering direct or indirect targets of transcription factors using ChIP-chip or ChIP-seq, and microarray or RNA-seq gene expression data. Inputting a list of genes of potential targets of one TF from ChIP-chip or ChIP-seq, and the gene expression results, GeneNetworkBuilder generates a regulatory network of the TF. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/GeneNetworkBuilder.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTPaul ShannonMore than 2000 annotated position frequency matrices from five public source, for multiple organisms <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/MotifDb.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTGeorge WuChIPXpress takes as input predicted TF bound genes from ChIPx data and uses a corresponding database of gene expression profiles downloaded from NCBI GEO to rank the TF bound targets in order of which gene is most likely to be functional TF target. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/ChIPXpress.html">link</a>Sat, 1 Jan 2012 00:00:00 GMTMichael Stravs, Emma SchymanskiWorkflow to process tandem MS files and build MassBank records. Functions include automated extraction of tandem MS spectra, formula assignment to tandem MS fragments, recalibration of tandem MS spectra with assigned fragments, spectrum cleanup, automated retrieval of compound information from Internet databases, and export to MassBank records. <br/><a href="http://bioconductor.org/packages/2.13/bioc/html/RMassBank.html">link</a>