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https://bioconductor.org/packages//2.11/bioc/html/bridge.html

Software package to test for differentially expressed genes with microarray data. It can be used with both cDNA microarrays or Affymetrix chip. The packge fits a robust Bayesian hierarchical model for testing for differential expression. Outliers are modeled explicitly using a $t$-distribution. The model includes an exchangeable prior for the variances which allow different variances for the genes but still shrink extreme empirical variances. The model can be used for testing for differentially expressed genes among multiple samples, and can distinguish between the different possible patterns of differential expression when there are three or more samples. Parameter estimation is carried out using a novel version of Markov Chain Monte Carlo that is appropriate when the model puts mass on subspaces of the full parameter space.

Proper citation: bridge (RRID:SCR_001343) Copy   

•   Source: SciCrunch Registry

https://www.bioconductor.org/packages//2.12/bioc/html/CALIB.html

Software package that contains functions for normalizing spotted microarray data, based on a physically motivated calibration model. The model parameters and error distributions are estimated from external control spikes.

Proper citation: CALIB (RRID:SCR_001338) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/LPE.html

Software library used to do significance analysis of microarray data with small number of replicates. It uses resampling based FDR adjustment, and gives less conservative results than traditional "BH" or "BY" procedures. Data accepted is raw data in txt format from MAS4, MAS5 or dChip. Data can also be supplied after normalization. LPE library is primarily used for analyzing data between two conditions.

Proper citation: LPE (RRID:SCR_001364) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/aroma.light.html

Light-weight software package for normalization and visualization of microarray data using only basic R data types. Software can be used standalone, be utilized in other packages, or be wrapped up in higher-level classes.

Proper citation: aroma.light (RRID:SCR_001312) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.13/bioc/html/cqn.html

A normalization tool for RNA-Seq data, implementing the conditional quantile normalization method.

Proper citation: CQN (RRID:SCR_001786) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/TDARACNE.html

Software package to infer gene regulatory networks from time-series measurements. The algorithm is expected to be useful in reconstruction of small biological directed networks from time course data.

Proper citation: TDARACNE (RRID:SCR_000498) Copy   

•   Source: SciCrunch Registry

http://mfuzz.sysbiolab.eu/

Software package for noise-robust soft clustering of gene expression time-series data (including a graphical user interface)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Mfuzz (RRID:SCR_000523) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/release/bioc/html/Rdisop.html

Software for identification of metabolites using high precision mass spectrometry. MS Peaks are used to derive a ranked list of sum formulae, alternatively for a given sum formula the theoretical isotope distribution can be calculated to search in MS peak lists.

Proper citation: Rdisop (RRID:SCR_000453) Copy   

•   Source: SciCrunch Registry