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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/nnNorm.html

Software package that allows to detect and correct for spatial and intensity biases with two-channel microarray data. The normalization method implemented in this package is based on robust neural networks fitting.

Proper citation: nnNorm (RRID:SCR_001354) Copy   

•   Source: SciCrunch Registry

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

Software that graphically displays correlation in microarray data that is due to insufficient normalization.

Proper citation: maCorrPlot (RRID:SCR_001348) 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.bioinf.jku.at/software/farms/farms.html

Software using a model-based technique for summarizing high-density oligonucleotide array data at probe level for Affymetrix GeneChips. It is based on a factor analysis model for which a Bayesian maximum a posteriori method optimizes the model parameters under the assumption of Gaussian measurement noise.

Proper citation: FARMS (RRID:SCR_001344) Copy   

•   Source: SciCrunch Registry

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

Software package that allows to characterize the operating characteristics of a microarray experiment, i.e. the trade-off between false discovery rate and the power to detect truly regulated genes. The package includes tools both for planned experiments (for sample size assessment) and for already collected data (identification of differentially expressed genes).

Proper citation: OCplus (RRID:SCR_001342) 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/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://ausweb.scu.edu.au/aw06/papers/refereed/sefton/paper.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The Integrated Content Environment (ICE) is a free Word-processor based system that allows authors to work individually or collaboratively on material for the Web, CD and print. This free web content management system, produced by the University of Southern Queensland, was initially developed by staff at the university to produce course content for online and print delivery. It has also been used for general web site development, and to manage documents in project intranets.

Proper citation: Integrated Content Environment (RRID:SCR_001369) 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://cde.nlm.nih.gov/

A repository of Common Data Elements (CDE). The CDE is a standardized, precisely defined question, paired with a set of allowable responses, used systematically across different sites, studies, or clinical trials to ensure consistent data collection. Multiple CDEs (from one or more Collections) can be curated into Forms. Forms in the Repository might be original, or might recreate the format of real-world data collection instruments or case report forms. NIH has endorsed collections of CDEs that meet established criteria. NIH-endorsed CDEs are designated with a gold ribbon. Users can Browse NIH-Endorsed CDEs, Browse All CDEs, or Browse Forms.

Proper citation: NIH Common Data Element Repository (RRID:SCR_001390) 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.semantic-measures-library.org

Open source Java library dedicated to semantic measures computation and analysis. Tools based on the SML are also provided through the SML-Toolkit, a command line software giving access to some of the functionalities of the library. The SML and the toolkit can be used to compute semantic similarity and semantic relatedness between semantic elements (e.g. concepts, terms) or entities semantically characterized (e.g. entities defined in a semantic graph, documents annotated by concepts defined in an ontology).

Proper citation: Semantic Measures Library (RRID:SCR_001383) Copy   

•   Source: SciCrunch Registry

https://scicrunch.org/scicrunch/data/source/nlx_154697-1/search?q=*&l=

Integrated Animals is a virtual database currently indexing available animal strains and mutants from: AGSC (Ambystoma), BCBC (mice), BDSC (flies), CWRU Cystic Fibrosis Mouse Models (mice), DGGR (flies), FlyBase (flies), IMSR (mice), MGI (mice), MMRRC (mice), NSRRC (pig), NXR (Xenopus), RGD (rats), Sperm Stem Cell Libraries for Biological Research (rats), Tetrahymena Stock Center (Tetrahymena), WormBase (worms), XGSC (Xiphophorus), ZFIN (zebrafish), and ZIRC (zebrafish).

Proper citation: Integrated Animals (RRID:SCR_001421) Copy   

•   Source: SciCrunch Registry

http://www.jcu.edu.au/

Public university in Townsville, Australia that functions as a research and teaching institution. Some well-known divisions of the university include the division of Tropical Environments and Societies, Tropical Health and Medicine, and Research and Innovation.

Proper citation: James Cook University; Townsville; Australia (RRID:SCR_001420) Copy   

•   Source: SciCrunch Registry

http://cismm.cs.unc.edu/

Biomedical technology research center that develops force technologies applicable over a wide range of biological settings, from the single molecule to the tissue, with integrated systems that orchestrate facile instrument control, multimodal imaging, and analysis through visualization and modeling. The Force Microscope Technologies Core designs instruments in an area of science where there are unusual opportunities: the measurement of forces and the integration with optical microscopy. Force technologies play the obvious role of both measuring events in the sample and modifying the sample during the experiment. It is through the microscope that the force data is correlated with simultaneous 3D optical images. The force technology development includes the magnetic bead technology in the 3D Force Microscope project, Atomic Force Microscopy in the nanoManipulator project, and Control Software to drive the instrumentation. This core is focused on providing the physical capability to perform the experiments and probe structure/property correlations. The Ideal User Interfaces core makes the connection between the user and the instrument, the model building, and the data. This includes control systems that allow the user to move the bead inside the cell culture with a handheld pen and the visualization techniques to view the optical microscope data as a rendered 3D image collocated with the force data. Using data to create, change, and understand a model is the focus of the Advanced Model Fitting and Analysis core. The quantitative reduction of images to structural, shape, and velocity parameters is the goal of Image Analysis. The immediate understanding of correlations across image fields and between data sets in the challenge of Visualization. The power of combining the strength of a computer science graphics group with a microscopy technology group is most evident in the Graphics Hardware Acceleration project, which seeks to harness the speed of graphics processors for microscope data analysis and simulation. The Advanced Technology core pushes the boundaries of the Human Computer Interface through the investigation of improved techniques for the interaction of users with virtual environments, the real time lighting of virtual settings, and the enabling of multi-person collaboration. These techniques are validated and evaluated through physiological measures in virtual environments effectiveness evaluation studies.

Proper citation: Computer Integrated Systems for Microscopy and Manipulation (RRID:SCR_001413) Copy   

•   Source: SciCrunch Registry