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http://cgap.nci.nih.gov/

Project to determine the gene expression profiles of normal, precancer, and cancer cells, whose generated resources are available to the cancer community. Interconnected modules provide access to all CGAP data, bioinformatic analysis tools, and biological resources allowing the user to find in silico answers to biological questions in a fraction of the time it once took in the laboratory. * Genes * Tissues * Pathways * RNAi * Chromosomes * SAGE Genie * Tools

Proper citation: Cancer Genome Anatomy Project (RRID:SCR_003072) Copy   

•   Source: SciCrunch Registry

https://github.com/phillipnicol/scGBM

Software application for model-based dimensionality reduction of scRNA-seq data. Quantifies uncertainty in each cell's latent position and leverages these uncertainties to assess confidence associated with given cell clustering. On real and simulated single-cell data produces low-dimensional embeddings that better capture relevant biological information while removing unwanted variation. Used for model-based dimensionality reduction for single-cell RNA-seq with generalized bilinear models.

Proper citation: scGBM (RRID:SCR_025518) Copy   

•   Source: SciCrunch Registry

https://spatialge.moffitt.org/

Web application, a user friendly, point-and-click implementation of spatialGE R package. Contains collection of methods for visualization and spatial statistics analysis of tissue microenvironment and heterogeneity using spatial transcriptomics experiments. Used for user-friendly analysis of spatial transcriptomics data.

Proper citation: Moffitt spatialGE (RRID:SCR_025980) Copy   

•   Source: SciCrunch Registry

https://github.com/STAR-Fusion/STAR-Fusion

Software tool to leverage chimeric and discordant read alignments identified by STAR aligner to predict fusions. Component of Trinity Cancer Transcriptome Analysis Toolkit. Used to identify candidate fusion transcripts supported by Illumina reads. Maps junction reads and spanning reads to reference annotation set.

Proper citation: STAR-Fusion (RRID:SCR_025853) Copy   

•   Source: SciCrunch Registry

https://cbc.app.vumc.org/tnbc/

Website for predicting the subtype of triple negative breast cancer sample based on its gene expression profile.

Proper citation: TNBCtype (RRID:SCR_026238) Copy   

•   Source: SciCrunch Registry

https://github.com/PhysiCell-Tools/PhysiCell-Studio

Software graphical tool to allow easy editing of (XML) model, create initial positions of cells, run simulation, and visualize results. To contribute, fork and make PRs to the development branch. Used to create, execute, and visualize multicellular model using PhysiCell.

Proper citation: PhysiCell Studio (RRID:SCR_025311) Copy   

•   Source: SciCrunch Registry

https://github.com/higlass/higlass

Web-based visual exploration and analysis of genome interaction maps.

Proper citation: HiGlass (RRID:SCR_026687) Copy   

•   Source: SciCrunch Registry

https://github.com/mskilab-org/JaBbA

Software tool to infer junction-balanced genome graphs with high fidelity. Builds genome graph based on junctions and read depth from whole genome sequencing, inferring optimal copy numbers for both vertices (DNA segments) and edges (bonds between segments).

Proper citation: JaBba (RRID:SCR_027134) Copy   

•   Source: SciCrunch Registry

https://sourceforge.net/projects/sivic/

Software framework and application suite for processing and visualization of DICOM MR Spectroscopy data. Through the use of DICOM, SIVIC aims to facilitate the application of MRS in medical imaging studies.

Proper citation: Spectroscopic Imaging, VIsualization, and Computing (SIVIC) (RRID:SCR_027875) Copy   

•   Source: SciCrunch Registry

https://github.com/QTIM-Lab/DeepNeuro

Software Python package for neuroimaging data. Framework to design and train neural network architectures. Used in medical imaging community to ensure consistent performance of networks across variable users, institutions, and scanners.

Proper citation: DeepNeuro (RRID:SCR_016911) Copy   

•   Source: SciCrunch Registry

https://github.com/plaisier-lab/sygnal

Software pipeline to integrate correlative, causal and mechanistic inference approaches into unified framework that systematically infers causal flow of information from mutations to TFs and miRNAs to perturbed gene expression patterns across patients. Used to decipher transcriptional regulatory networks from multi-omic and clinical patient data. Applicable for integrating genomic and transcriptomic measurements from human cohorts.

Proper citation: SYGNAL (RRID:SCR_023080) Copy   

•   Source: SciCrunch Registry

https://github.com/qianli10000/mtradeR

Software R package implements Joint model with Matching and Regularization and simulation pipeline. Used to test association between taxa and disease risk, and adjusted for correlated taxa screened by pre-selection procedure in abundance and prevalence, individually.

Proper citation: mtradeR (RRID:SCR_022977) Copy   

•   Source: SciCrunch Registry

https://github.com/Shenhav-and-Korem-labs/SCRuB

Software R package to help researchers address common issue of contamination in microbial studies. Well aware MiSeq decontamination program.

Proper citation: SCRuB (RRID:SCR_023518) Copy   

•   Source: SciCrunch Registry

https://pancreatlas.org/

Collection of human pancreas data and images. Platform to share data from human pancreas samples. Houses reference datasets from human pancreas samples, achieved through generosity of organ donors and their families.

Proper citation: Pancreatlas (RRID:SCR_018567) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/annotare/

A software tool for annotating biomedical investigations and the resulting data, then producing a MAGE-TAB file. This software is a standalone desktop which features: an editor function, an annotation modifier, incorporation of terms from biomedical ontologies, standard templates for common experiment types, a design aid to help create a new document, and a validator that checks for syntactic and semantic violations.

Proper citation: Annotare (RRID:SCR_000319) Copy   

•   Source: SciCrunch Registry

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

Software R package to model and impute non-detects in results of qPCR experiments.Used to directly model non-detects as missing data.

Proper citation: nondetects (RRID:SCR_001702) Copy   

•   Source: SciCrunch Registry

https://cytotrace.stanford.edu/

Software tool that predicts differentiation state of cells from single cell RNA sequencing data. Used for predicting differentiation states from scRNA-seq data.

Proper citation: CytoTRACE (RRID:SCR_022828) Copy   

•   Source: SciCrunch Registry

http://www.rhesusbase.org/drugDisc/CAM.jsp

OKCAM (Ontology-based Knowledgebase for Cell Adhesion Molecules) is an online resource for human genes known or predicted to be related to the processes of cell adhesion. These genes include members of the cadherin, immunoglobulin/FibronectinIII (IgFn), integrin, neurexin, neuroligin, and catenin families. Totally 496 human CAM genes were compiled and annotated. We have mapped these genes onto a novel cell adhesion molecule ontology (CAMO) that provides a hierarchical description of cell adhesion molecules and their functions. It is intended to provide a means to facilitate better and better understanding of the global and specific properties of CAMs through their genomic features, regulatory modes, expression patterns and disease associations become clearer. You may browse by CAM ontology, Chromosomes and Full Gene list.

Proper citation: OKCAM: Ontology-based Knowledgebase for Cell Adhesion Molecules (RRID:SCR_010696) Copy   

•   Source: SciCrunch Registry

https://github.com/mskcc/facets

Software tool for estimating genome copy numbers from high throughput DNA sequencing data. Allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing. Used to implement Fraction and Copy number Estimate from Tumor/normal Sequencing.

Proper citation: FACETS (RRID:SCR_026264) Copy   

•   Source: SciCrunch Registry

http://www.cidr.jhmi.edu/

Next generation sequencing and genotyping services provided to investigators working to discover genes that contribute to disease. On-site statistical geneticists provide insight into analysis issues as they relate to study design, data production and quality control. In addition, CIDR has a consulting agreement with the University of Washington Genetics Coordinating Center (GCC) to provide statistical and analytical support, most predominantly in the areas of GWAS data cleaning and methods development. Completed studies encompass over 175 phenotypes across 530 projects and 620,000 samples. The impact is evidenced by over 380 peer-reviewed papers published in 100 journals. Three pathways exist to access the CIDR genotyping facility: * NIH CIDR Program: The CIDR contract is funded by 14 NIH Institutes and provides genotyping and statistical genetic services to investigators approved for access through competitive peer review. An application is required for projects supported by the NIH CIDR Program. * The HTS Facility: The High Throughput Sequencing Facility, part of the Johns Hopkins Genetic Resources Core Facility, provides next generation sequencing services to internal JHU investigators and external scientists on a fee-for-service basis. * The JHU SNP Center: The SNP Center, part of the Johns Hopkins Genetic Resources Core Facility, provides genotyping to internal JHU investigators and external scientists on a fee-for-service basis. Data computation service is included to cover the statistical genetics services provided for investigators seeking to identify genes that contribute to human disease. Human Genotyping Services include SNP Genome Wide Association Studies, SNP Linkage Scans, Custom SNP Studies, Cancer Panel, MHC Panels, and Methylation Profiling. Mouse Genotyping Services include SNP Scans and Custom SNP Studies.

Proper citation: Center for Inherited Disease Research (RRID:SCR_007339) Copy   

•   Source: SciCrunch Registry