REVEAL Solutions

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.

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REVEAL Solutions are immediately available for specific research use cases by providing GUI’s, R and Python API’s, and notebooks with extensive documentation. Built-in, automated elastic computing provides the most cost effective solution on the market. Get a head start with datasets, metadata, data models, reference data, and workflows for efficient exploration, retrieval, and analytics.

REVEAL leverages FAIR principles to transform the pace of daily research.


Searchable by any metadata, reference data, ontology, or data values. Intuitively organized data management: ETL, QA, and organize once, use repeatably.


All data are accessible by their unique identifier along with an open protocol for retrieving metadata and data. REST, R, and Python APIs enable retrieving data across datasets.


REST, R, and Python APIs return data in whatever formats are required for downstream analysis. Structured data, unstructured data, images, and industry-specialized file formats work seamlessly together.


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.

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Papers and Posters

Explore the latest papers and posters about REVEAL Solutions

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Assessing the impact and scalability of batch correction algorithms on a heterogeneous single cell atlas.

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ASHG: Mitigating challenges of large-scale single cell data management, querying, and analysis with REVEAL: SingleCell

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ASHG: Scalable mQTL analysis of biochemical pathways with the UK Biobank data (project 51518) in REVEAL: Biobank

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Featured Download

Examination of a methylation-driven breast cancer gene panel using UK Biobank, TCGA, and single cell Human Cell Atlas datasets – presented at the American Society of Human Genetics Conference 2022.