REVEAL Solutions maximize the productivity of limited bioinformatics and data scientist resources with out-of-the box solutions for current challenges in translational data science.
Metadata and data are well-described with provenance so that they can be replicated and/or combined in different settings.
Versioning of data, algorithms, genome assembly, reference datasets, ontologies, and computing environment along with logging, provenance and permissions support reusability.
REVEAL: SingleCell is designed to be the point of truth for spatial and suspension single cell data, including images, enabling scalable cohort selection and analytics at patient population scales, billions of cells.
Findable: View and explore hundreds of single cell multiomics datasets (e.g., RNA-seq, CITE-seq, Spatial Transcriptomics) through R, Python, and REST APIs.
Accessible: Run analytical queries and algorithms across datasets and millions of cells within user friendly and intuitive interfaces (e.g., search expression for gene signatures, run batch correction at scale, find all macrophage cells across hundreds of datasets).
Interoperable: Use visualization tools and GUIs to analyze results and correlate findings in multiomics data such as spatial transcriptomics.
Reusable: Organized storage of data removes repeated ETL overhead. Create custom precision cell atlases (e.g., kidney cells) that can be versioned and annotated for specific downstream analysis.
Immediately available Population Scale Data
Immediately available solution to centralize all single cell data
Ease of use with low code
Data management layer with schema tailored for fast retrieval and compute based on metadata and scalability to 100s of TBs of data
Domain expert workflows
Extensible: Build your own workflows in Python or R
APIs to retrieve data in a format that can be integrated with other data and return data in whatever formats are required by downstream analysis: e.g. data frames in python or R; parquet files, bioinformatic-specific formats
Interoperable with flexFS and AI/ML packages
Integrated provenance, versioning, traceability, and logs
Granular, slice-level access control
Public Data Sets
Publicly available datasets available pre-loaded for simplified validation
Explore the latest papers and posters about REVEAL Solutions
Assessing the impact and scalability of batch correction algorithms on a heterogeneous single cell atlas.
ASHG: Mitigating challenges of large-scale single cell data management, querying, and analysis with REVEAL: SingleCell
ASHG: Scalable mQTL analysis of biochemical pathways with the UK Biobank data (project 51518) in REVEAL: Biobank