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http://bioconductor.org/packages/devel/bioc/html/massiR.html

Software that predicts the sex of samples in gene expression microarray datasets.

Proper citation: massiR (RRID:SCR_001157) Copy   

•   Source: SciCrunch Registry

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

Software package for quality control of Affymetrix GeneChip expression data and reproducibility analysis of human whole genome chips with the MAQC reference datasets.

Proper citation: yaqcaffy (RRID:SCR_001295) Copy   

•   Source: SciCrunch Registry

http://julian-gehring.github.io/les/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software package that estimates Loci of Enhanced Significance (LES) in tiling microarray data. These are regions of regulation such as found in differential transcription, CHiP-chip, or DNA modification analysis. The package provides a universal framework suitable for identifying differential effects in tiling microarray data sets, and is independent of the underlying statistics at the level of single probes.

Proper citation: les (RRID:SCR_001291) Copy   

•   Source: SciCrunch Registry

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

Software package for non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. Tests based on a variety of t- and F-statistics (including t-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with t-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted p-values, confidence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments.

Proper citation: multtest (RRID:SCR_001255) Copy   

•   Source: SciCrunch Registry

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

Software package for quantile smoothing and genomic visualization of array data.

Proper citation: quantsmooth (RRID:SCR_001271) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.0/bioc/html/SNPchip.html

Software package that contains classes and methods useful for storing, visualizing and analyzing high density SNP data. Originally developed from the SNPscan web-tool, SNPchip utilizes S4 classes and extends other open source R tools available at Bioconductor, including the R packages Biobase and oligo. This has numerous advantages, including the ability to build statistical models for SNP-level data that operate on instances of the class, and to communicate with other R packages that add additional functionality.

Proper citation: SNPchip (RRID:SCR_001269) Copy   

•   Source: SciCrunch Registry

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

Software R package for Gaussian Process Ranking and Estimation of Gene Expression time-series. The software fits two Gaussian processes (GPs) with an radial basis function (RBF) (+ noise diagonal) kernel on each profile. One GP kernel is initialized wih a short lengthscale hyperparameter, signal variance as the observed variance and a zero noise variance. It is optimized via scaled conjugate gradients (netlab). A second GP has fixed hyperparameters: zero inverse-width, zero signal variance and noise variance as the observed variance. The log-ratio of marginal likelihoods of the two hypotheses acts as a score of differential expression for the profile. Comparison via receiver operating characteristic curves (ROC curves) is performed against Bayesian hierarchical model for the analysis of time-series (BATS) (Angelini et.al, 2007).

Proper citation: gprege (RRID:SCR_001324) Copy   

•   Source: SciCrunch Registry

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

Software package to read bead-level data (raw TIFFs and text files) output by BeadScan as well as bead-summary data from BeadStudio. Methods for quality assessment and low-level analysis are provided.

Proper citation: beadarray (RRID:SCR_001314) Copy   

•   Source: SciCrunch Registry

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

Software library that contains functions to investigate links between differential gene expression and the chromosomal localization of the genes. It is motivated by the common observation of phenomena involving large chromosomal regions in tumor cells. MACAT is the implementation of a statistical approach for identifying significantly differentially expressed chromosome regions.

Proper citation: MACAT (RRID:SCR_001350) Copy   

•   Source: SciCrunch Registry

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

Software to identify differentially expressed genes. A hierarchical Bayesian approach is used, and the hyperparameters are estimated using empirical Bayes.

Proper citation: lapmix (RRID:SCR_001347) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/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

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

http://itb.biologie.hu-berlin.de/~futschik/software/R/OLIN/index.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

http://www.bioconductor.org/packages/release/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

https://github.com/yongchao/flowPeaks

Software for fast and automatic clustering to classify the cells into subpopulations based on finding the peaks from the overall density function generated by K-means.

Proper citation: flowPeaks (RRID:SCR_000407) 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).

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