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Welcome to OpenCGA

OpenCGA is an open-source project that aims to provide a Big Data storage engine and analysis framework for genomic scale data analysis of hundreds of terabytes

Main Features

  • High-performance and scalable variant storage and index to load and merge VCF/gVCF files
  • Annotate and calculate statistics for all the variants
  • Clinical interpretation analysis of samples and families
  • Client libraries developed in Java, Python, R and Javascript
  • Integrated Catalog keeps track of users, files, jobs, clinical data...
  • Interactive web-based data mining tool based on IVA


Latest news:

OpenCGA v1.2.0 Released
We are pleased to announce new version 1.2.0!



Metadata and Security

Metadata Database


Authenticated Environment


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. Current 

Many variant operations have been implemented such as variant aggregation, stats calculation, variant annotation, export, ...


Alignment Storage


Easy to Use

REST API and Clients


Command Line Interface








Clinical Analysis

Clinical Data

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.

Clinical Interpretation

We have implemented some automatic clinical interpretation algorithms for Rare Diseases 

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)

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