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http://www.bioconductor.org/packages/2.13/bioc/html/BeadDataPackR.html
Software that provides functionality for the compression and decompression of raw bead-level data from the Illumina BeadArray platform.
Proper citation: BeadDataPackR (RRID:SCR_001310) Copy
https://www.bioconductor.org/packages/release/bioc/html/OLIN.html
Software functions for normalization of two-color microarrays by optimised local regression and for detection of artifacts in microarray data.
Proper citation: OLIN (RRID:SCR_001304) Copy
http://www.bioconductor.org/packages/release/bioc/html/qcmetrics.html
Software package that provides a framework for generic quality control of data. It permits to create, manage and visualise individual or sets of quality control metrics and generate quality control reports in various formats.
Proper citation: qcmetrics (RRID:SCR_001303) Copy
https://www.bioconductor.org/packages//2.12/bioc/html/dexus.html
Software package that 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. It 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. It 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.
Proper citation: DEXUS (RRID:SCR_001309) Copy
http://www.bioconductor.org/packages/release/bioc/html/vsn.html
Software package that implements a method for normalizing microarray intensities, both between colours within array, and between arrays. The method uses a robust variant of the maximum-likelihood estimator for the stochastic model of microarray data described in the references. The model incorporates data calibration (a.k.a. normalization), a model for the dependence of the variance on the mean intensity, and a variance stabilizing data transformation. Differences between transformed intensities are analogous to normalized log-ratios. However, in contrast to the latter, their variance is independent of the mean, and they are usually more sensitive and specific in detecting differential transcription.
Proper citation: vsn (RRID:SCR_001459) Copy
http://www.bioconductor.org/packages/devel/bioc/html/CNVrd2.html
A software package that uses next-generation sequencing data to measure human gene copy number for multiple samples, indentify SNPs tagging copy number variants and detect copy number polymorphic genomic regions.
Proper citation: CNVrd2 (RRID:SCR_001723) Copy
http://bioconductor.org/packages/2.13/bioc/html/sSeq.html
Software package 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.
Proper citation: sSeq (RRID:SCR_001719) Copy
http://www.bioconductor.org/packages/2.12/bioc/html/PING.html
Software program for probabilistic inference of ChIP-Seq using an empirical Bayes mixture model approach.
Proper citation: PING (RRID:SCR_005394) Copy
http://www.bioconductor.org/packages/devel/bioc/html/DMRforPairs.html
Software for identifying differentially methylated regions between unique samples using array based methylation profiles. It allows researchers to compare n greater than or equal to 2 unique samples with regard to their methylation profile. The (pairwise) comparison of n unique single samples distinguishesit from other existing pipelines as these often compare groups of samples in either single CpG locus or region based analysis. DMRforPairs defines regions of interest as genomic ranges with sufficient probes located in close proximity to each other. Probes in one region are optionally annotated to the same functional class(es). Differential methylation is evaluated by comparing the methylation values within each region between individual samples and (if the difference is sufficiently large), testing this difference formally for statistical significance.
Proper citation: DMRforPairs (RRID:SCR_005702) Copy
http://bioconductor.org/packages/release/bioc/html/tweeDEseq.html
Software for differential expression analysis of RNA-seq using the Poisson-Tweedie family of distributions.
Proper citation: tweeDEseq (RRID:SCR_003038) Copy
http://bioconductor.org/packages/release/bioc/html/BRAIN.html
Software package for calculating aggregated isotopic distribution and exact center-masses for chemical substances (in this version composed of C, H, N, O and S).
Proper citation: BRAIN (RRID:SCR_003018) Copy
http://www.bioconductor.org/packages/release/bioc/html/survcomp.html
R package providing functions to assess and to compare the performance of risk prediction (survival) models.
Proper citation: SurvComp (RRID:SCR_003054) Copy
http://www.bioconductor.org/packages/release/bioc/html/ddCt.html
Software package providing an approximation method to determine relative gene expression with quantitative real-time PCR (qRT-PCR) experiments. It requires no standard curve for each primer-target pair, therefore reducing the working load and yet returning accurate enough results as long as the assumptions of the amplification efficiency hold. The package implements a pipeline to collect, analyze and visualize qRT-PCR results, for example those from TaqMan SDM software, mainly using the ddCt method. The pipeline can be either invoked by a script in command-line or through the API consisting of S4-Classes, methods and functions.
Proper citation: ddCt (RRID:SCR_003396) Copy
http://www.bioconductor.org/packages/release/bioc/html/ggbio.html
An R package for extending the grammar of graphics for genomic data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor data structures are supported, where appropriate. The package supports detailed views of particular genomic regions, as well as genome-wide overviews. Supported overviews include ideograms and grand linear views. High-level plots include sequence fragment length, edge-linked interval to data view, mismatch pileup, and several splicing summaries.
Proper citation: ggbio (RRID:SCR_003313) Copy
http://www.bioconductor.org/packages/devel/bioc/html/OmicCircos.html
An R software application and package used to generate high-quality circular plots for visualizing genomic variations, including mutation patterns, copy number variations (CNVs), expression patterns, and methylation patterns.
Proper citation: OmicCircos (RRID:SCR_003292) Copy
http://www.bioconductor.org/packages/release/bioc/html/unifiedWMWqPCR.html
Software package that implements the unified Wilcoxon-Mann-Whitney Test for qPCR data. This modified test allows for testing differential expression in qPCR data.
Proper citation: unifiedWMWqPCR (RRID:SCR_001706) Copy
http://www.bioconductor.org/packages/release/bioc/html/RSVSim.html
A software package for the simulation of deletions, insertions, inversions, tandem duplications and translocations of various sizes in any genome available as FASTA-file or data package in R. 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.
Proper citation: RSVSim (RRID:SCR_001777) Copy
http://www.bioconductor.org/packages/release/bioc/html/TCC.html
An R package that provides a series of functions for differential expression analysis from RNA-seq count data using robust normalization strategy (called DEGES). The basic idea of DEGES is that potential differentially expressed genes or transcripts (DEGs) among compared samples should be removed before data normalization to obtain a well-ranked gene list where true DEGs are top-ranked and non-DEGs are bottom ranked. This can be done by performing a multi-step normalization strategy (called DEGES for DEG elimination strategy). A major characteristic of TCC is to provide the robust normalization methods for several kinds of count data (two-group with or without replicates, multi-group/multi-factor, and so on) by virtue of the use of combinations of functions in other sophisticated packages (especially edgeR, DESeq, and baySeq).
Proper citation: TCC (RRID:SCR_001779) Copy
http://www.bioconductor.org/packages/release/bioc/html/SamSPECTRAL.html
Software that identifies cell population in flow cytometry data. It demonstrates significant advantages in proper identification of populations with non-elliptical shapes, low density populations close to dense ones, minor subpopulations of a major population and rare populations. It samples large data such that spectral clustering is possible while preserving density information in edge weights. More specifically, given a matrix of coordinates as input, SamSPECTRAL first builds the communities to sample the data points. Then, it builds a graph and after weighting the edges by conductance computation, the graph is passed to a classic spectral clustering algorithm to find the spectral clusters. The last stage of SamSPECTRAL is to combine the spectral clusters. The resulting connected components estimate biological cell populations in the data sample.
Proper citation: SamSPECTRAL (RRID:SCR_001858) Copy
http://www.bioconductor.org/packages/release/bioc/html/RchyOptimyx.html
Software that constructs a hierarchy of cells using flow cytometry for maximization of an external variable (e.g., a clinical outcome or a cytokine response).
Proper citation: RchyOptimyx (RRID:SCR_001889) Copy
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