OpenCGA
OverviewInstallationUsing OpenCGA
v2.1
v2.1
  • Home
  • Overview
    • Features
    • Architecture Diagram
    • Security
    • Metadata and Clinical Data
    • Data Models
      • Sample
      • Individual
    • Alignment and Coverage
    • Variant Query and Analysis
    • Clinical Data Analysis
    • Running Analysis
    • Scalability and Performance
    • Sizing OpenCGA
  • OpenCGA Architecture
    • Catalog
    • Alignment and Coverage
    • Variant Storage Engine
      • Variant Data Model
    • Clinical Analysis
    • Analysis Framework
  • Data Models
    • User
    • Project
    • Study
    • File
    • Sample
    • Individual
    • Family
    • Cohort
    • Job
    • Clinical Analysis
  • Case Studies
    • Genomics England Research
    • Microsoft Azure
  • User Manual
    • Installation
      • Kubernetes Cluster
        • Azure
        • Configuration
      • On-Premise HPC Cluster
        • Server Configuration
        • Getting OpenCGA
        • Choosing Variant Storage Engine
        • Configuration
      • Running Docker
    • Login
    • Using OpenCGA
      • REST Web Service API
      • IVA Web App
      • Client Libraries
        • pyopencga - Python Library
        • opencgaR - R library
        • Java
        • JavaScript
      • Command Line
        • Configuration
      • Public Demo
    • Managing Data
      • Sharing and Permissions
        • Users and Groups
        • Study ACLs
      • Create Projects and Studies
      • Load VCF Files to a Study
      • Working with Files
      • Population of Metadata
        • Adding Custom Metadata
        • Data Versioning
    • Alignment Engine
      • BAM Index
      • Alignment Read Query
      • Working with Coverage
      • Alignment Analysis
    • Variant Storage Engine
      • Variant Query
      • Variant Aggregation Stats
      • Variant Analysis
    • Clinical Genomics
      • Clinical Interpretation
      • Clinical Analysis
    • Using JupyterLab
    • Administrator
      • User Management
      • Templates / Manifest
  • About
    • Roadmap
    • Release Notes
    • Community
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Overview

OpenCGA is an open-source platform that aims to provide a full stack solution for big data analysis and visualisation of genomic data. OpenCGA has been designed to provide a secure, high-performance and scalable solution for genomics analysis and visualisation.

OpenCGA implements a complete solution that covers all aspects of genomic analysis: metadata database, authentication and security, variant normalisation and aggregation, variant storage and annotation, highly scalable variant NoSQL storage engine, alignment and coverage, big data variant analysis, RESTful web services, visualisation

OpenCGA is developed and maintained in the University of Cambridge and it is currently used by several big data projects such as GEL (Genomics England).

Main Features

OpenCGA provides a complete solution for genomics data analysis:

  • Authenticated and secure platform to query and visualise data, advanced permission system

  • A metadata database to keep track of registered users, projects, studies, files, samples, families, jobs,

  • Clinical data from sample, patients or families

  • Alignment storage allows to index BAM/CRAM, calculate index and query data and coverage

  • The most advanced, high-performance and scalable Variant storage solution, you can normalise, load, index and aggregate thousands of whole genomes per day

  • Genomic Analysis implemented on top of variant and alignment storage layer using advanced technologies such as Spark

  • Full clinical analysis platform implemented, you can create the cases and run different clinical interpretations algorithms from your scripts or from a web application

  • Comprehensive RESTful web service API with more than 150 endpoints to fully query and manage all metadata and clinical data

  • Four different client libraries implemented in Java, Python, R and Javascript

  • Interactive web-based application for the analysis and visualisation of variants and reads

Projects

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Last updated 3 years ago

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OpenCGA is used by several projects being the most important .

Genomics England (NHS)