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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://www.broadinstitute.org/
Biomedical and genomic research center located in Cambridge, Massachusetts, United States. Nonprofit research organization under the name Broad Institute Inc., and is partners with Massachusetts Institute of Technology, Harvard University, and the five Harvard teaching hospitals. Dedicated to advance understanding of biology and treatment of human disease to improve human health.
Proper citation: Broad Institute (RRID:SCR_007073) Copy
https://cirrocumulus.readthedocs.io/en/stable/
Web interactive visualization tool for large scale single cell genomics data.Interactive web application for exploring million scale single cell datasets. Can be hosted on Google App Engine application for collaborative use or can be run in standalone mode on personal computer. Consists of client side component implemented in JavaScript and server component implemented in Python. Client uses React to manage state and WebGL to visualize variables on 2D/3D embeddings in performant manner. Server component consists of functions to manage datasets, slice variables from dataset stored in PARQUET, Zarr or H5AD formats.
Proper citation: Cirrocumulus (RRID:SCR_021646) Copy
Open ecosystem of data repositories hosted by various partner organizations, who work together to ensure that their data can be federated across participating platforms. Open source platform for biomedical researchers to access data, run analysis tools, and collaborate. Terra powers important scientific projects including AnVIL, BioData Catalyst, Human Cell Atlas, BICCN, and many others. Easily access both open and access-controlled datasets hosted in cloud repositories. Explore, analyze, and visualize data using Jupyter Notebooks, RStudio, RShinyApps, and Galaxy.
Proper citation: Terra (RRID:SCR_021648) Copy
https://pegasus.readthedocs.io/en/stable
Software package for massive single cell data processing. Enables analysis of million scale single cell RNA-seq data and is functionally comparable to Seurat and SCANPY. Command line tool, Python package and base for Cloud based analysis workflows. Supports variety of analysis tasks, such as cell and gene level quality control, highly variable gene selection, dimension reduction, kNN graph building, data integration, clustering, differential expression analysis and putative cell type annotation.
Proper citation: Pegasus (RRID:SCR_021645) Copy
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The NIDDK Information Network (dkNET) serves the needs of basic and clinical investigators by providing seamless access to large pools of data and research resources relevant to the mission of The National Institute of Diabetes Digestive and Kidney Diseases (NIDDK). dkNET is hosted at University of California San Diego, and is supported by NIH NIDDK grant U24DK097771.
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