Metadata and Security
Metadata Database
OpenCGA Catalog implements a high-performance metadata database to track all files metadata, samples, families, ...
Authenticated Environment
Security
Variant and Alignment Storage
Variant Database
OpenCGA implements a high-performance and scalable variant NoSQL database to store and index thousands of whole genome VCF files. Performance observed show more than 2,000 whole genomes indexed a day.
Many variant operations have been implemented such as variant aggregation, stats calculation, variant annotation, export, ...
We have implemented the most advanced query engine and aggregation framework to query variants.
Alignment Storage
Indexing BAM files and calculating coverage is supported. You can efficiently query all these data through REST web services.
Easy to Use
REST API and Clients
We have implemented a comprehensive REST API to work with Catalog and query Variants and Alignment data in a secure way. To facilitate using REST we have developed four client libraries developed in Java, Python, R and Javascript.
Command Line Interface
Clinical Analysis
Clinical Data and Disease Panels
You can store all you clinical data in our free data model solution in Catalog. You can define your clinical variables and annotate files, samples, individuals, families or cohort. Clinical Data is indexed automatically to provide a real-time queries and aggregations analysis.
Disease Panels are fully supported and versioned.
Clinical Interpretation Analysis
You can define different types of Clinical Analysis. We have implemented some automatic clinical interpretation algorithms for Rare Diseases (families) and Cancer. A Decision Support System has also been implemented in IVA.
Big Data Analysis
Rich Data Models
Spark Analysis
Visualisation
Source Code
Web based on IVA project at https://github.com/opencb/iva/tree/app/hgva
Server based on OpenCGA at https://github.com/opencb/opencga
Contributing
IVA is a collaborative project that aims to integrate as many reference human studies as possible, you can contact us for feature request. If you want to contribute to the code you are more than welcome to contribute to IVA and OpenCGA
Contributors
Ignacio Medina (HPCS, University of Cambridge)
Dr. Augusto Rendon (Genomics England)
Development
Source Code
Web based on IVA project at https://github.com/opencb/iva/tree/app/hgva
Server based on OpenCGA at https://github.com/opencb/opencga
Contributing
IVA is a collaborative project that aims to integrate as many reference human studies as possible, you can contact us for feature request. If you want to contribute to the code you are more than welcome to contribute to IVA and OpenCGA
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