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http://www.cbioc.com/en/

Commercial organization that discovers, validates & analyzes genomic biomarkers with a focus on body fluid samples. Take advantage of their proven expertise in biomarker signature development and speed up your biomarker studies.

Proper citation: Comprehensive Biomarker Center (RRID:SCR_003901) Copy   

•   Source: SciCrunch Registry

http://www.flexgen.nl/

A biotechnology company that has developed technology for synthesizing custom microarrays, the FlexArrayer. Its is a desk-top sized instrument which allows the researcher to generate, in their own laboratory, either a custom oligonucleotide array in a single day or oligonucleotide pool in a few days. Recent developments in synthesis chemistry allows many modifications to be incorporated or for alternative chemistries to be considered.

Proper citation: FlexGen (RRID:SCR_003902) Copy   

•   Source: SciCrunch Registry

http://www.cxrbiosciences.com/

Commercial organization that provides preclinical services and expertise, specializing in investigative toxicology, exploratory and discovery toxicology, metabolism and pharmacokinetics. CXR Biosciences is now Concept Life Sciences.

Proper citation: CXR Biosciences (RRID:SCR_003961) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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

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 (enrichment) analysis tools for large-scale and fully automated analysis.

Proper citation: Pathview (RRID:SCR_002732) Copy   

•   Source: SciCrunch Registry

http://medgene.med.harvard.edu/MEDGENE/

An algorithm that generates lists of genes associated with a gene or one or more disorders. The algorithm can be used in high-throughput screening experiments, can create disease-specific micro-arrays, and can sort the results of gene profiling data. Based on the co-citations of all Medline records, MedGene can retrieve the following relationships: 1. A list of human genes associated with a particular human disease in ranking order 2. A list of human genes associated with multiple human diseases in ranking order 3. A list of human diseases associated with a particular human gene in ranking order 4. A list of human genes associated with a particular human gene in ranking order 5. The sorted gene list from other disease related high-throughput experiments, such as micro-array 6. The sorted gene list from other gene related high-throughput experiments, such as micro-array

Proper citation: MedGene (RRID:SCR_008122) 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).

Proper citation: Mfuzz (RRID:SCR_000523) Copy   

•   Source: SciCrunch Registry

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://www.bioconductor.org/packages/release/bioc/html/methyAnalysis.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software package for 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 focuses on analyzing the Illumina Infinium methylation array data, but most methods can be generalized to other methylation array or sequencing data.

Proper citation: methyAnalysis (RRID:SCR_001290) 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://www.bioconductor.org/packages/release/bioc/html/ITALICS.html

Software package to normalize of Affymetrix GeneChip Human Mapping 100K and 500K set.

Proper citation: ITALICS (RRID:SCR_001274) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.14/bioc/html/mBPCR.html

Software package that estimates the DNA copy number profile to detect regions with copy number changes.

Proper citation: mBPCR (RRID:SCR_001273) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/devel/bioc/html/CGHregions.html

Software package for dimension Reduction for Array CGH Data with Minimal Information Loss.

Proper citation: CGHregions (RRID:SCR_001278) 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/2.1/bioc/html/VanillaICE.html

Software package using Hidden Markov Models for characterizing chromosomal alterations in high throughput SNP arrays.

Proper citation: VanillaICE (RRID:SCR_001268) Copy   

•   Source: SciCrunch Registry

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

Software package that provides a pipeline for gene expression analysis (primarily for RNA-Seq data). The normalization function is specific for RNA-Seq analysis, but all other functions (Quality Control Figures, Differential Expression and Visualization, and Functional Enrichment via BD-Func) will work with any type of gene expression data.

Proper citation: sRAP (RRID:SCR_001297) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/SCAN.UPC.html

A microarray normalization software (SCAN) to facilitate personalized-medicine workflows with an extension (UPC) that estimates whether a given gene/transcript is active above background levels in a given sample. 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 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. A

Proper citation: SCAN.UPC (RRID:SCR_001334) Copy   

•   Source: SciCrunch Registry