Skip to main content

A REST client for OpenCGA REST web services

Project description

PyOpenCGA

This Python client package makes use of the comprehensive RESTful web services API implemented for the OpenCGA platform. OpenCGA is an open-source project that implements a high-performance, scalable and secure platform for Genomic data analysis and visualisation

OpenCGA implements a secure and high performance platform for Big Data analysis and visualisation in current genomics. OpenCGA uses the most modern and advanced technologies to scale to petabytes of data. OpenCGA is designed and implemented to work with few million genomes. It is built on top of three main components: Catalog, Variant and Alignment Storage and Analysis.

More info about this project in the OpenCGA Docs

Installation

Cloning

PyOpenCGA can be cloned in your local machine by executing in your terminal:

$ git clone https://github.com/opencb/opencga.git

Once you have downloaded the project you can install the library. We recommend to install it inside a virtual environment:

$ cd opencga/tree/develop/opencga-client/src/main/python/pyOpenCGA
$ python setup.py install

Pip install

Run the following command in the shell:

$ pip install pyopencga

Usage

Import pyOpenCGA package

The first step is to import the ClientConfiguration and OpenCGAClient from pyOpenCGA:

>>> from pyopencga.opencga_config import ClientConfiguration
>>> from pyopencga.opencga_client import OpenCGAClient

Setting up server host configuration

The second step is to generate a ClientConfiguration instance by passing a configuration dictionary containing the host to point to or a client-configuration.yml file:

>>> config = ClientConfiguration('/opt/opencga/conf/client-configuration.yml')
>>> config = ClientConfiguration({
        "rest": {
                "host": "http://bioinfo.hpc.cam.ac.uk/opencga-demo"
        }
    })

Log in to OpenCGA host server

With this configuration you can initialize the OpenCGAClient, and log in:

>>> oc = OpenCGAClient(config)
>>> oc.login('user')

For scripting or using Jupyter Notebooks is preferable to load user credentials from an external JSON file.

Once you are logged in, it is mandatory to use the token of the session to propagate the access of the clients to the host server:

>>> token = oc.token
>>> print(token)
eyJhbGciOi...

>>> oc = OpenCGAClient(configuration=config_dict, token=token)

Examples

The next step is to get an instance of the clients we may want to use:

>>> projects = oc.projects # Project client
>>> studies = oc.studies   # Study client
>>> samples = oc.samples # Sample client
>>> cohorts = oc.cohorts # Cohort client

Now you can start asking to the OpenCGA RESTful service with pyOpenCGA:

>>> for project in projects.search(owner=user).get_results():
...    print(project['id'])
project1
project2
[...]

There are two different ways to access to the query response data:

>>> foo_client.method().get_results() # Iterates over all the results of all the QueryResults
>>> foo_client.method().get_responses() # Iterates over all the responses

Data can be accessed specifying comma-separated IDs or a list of IDs:

>>> samples = 'NA12877,NA12878,NA12879'
>>> samples_list = ['NA12877','NA12878','NA12879']
>>> sc = oc.samples

>>> for result in sc.info(query_id=samples, study='user@project1:study1').get_results():
...     print(result['id'], result['attributes']['OPENCGA_INDIVIDUAL']['disorders'])
NA12877 [{'id': 'OMIM6500', 'name': "Chron's Disease"}]
NA12878 []
NA12879 [{'id': 'OMIM6500', 'name': "Chron's Disease"}]

>>> for result in sc.info(query_id=samples_list, study='user@project1:study1').get_results():
...     print(result['id'], result['attributes']['OPENCGA_INDIVIDUAL']['disorders'])
NA12877 [{'id': 'OMIM6500', 'name': "Chron's Disease"}]
NA12878 []
NA12879 [{'id': 'OMIM6500', 'name': "Chron's Disease"}]

Optional filters and extra options can be added as key-value parameters (where the values can be a comma-separated string or a list).

What can I ask for?

The best way to know which data can be retrieved for each client check OpenCGA web services swagger.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyopencga-2.12.3.tar.gz (64.6 kB view details)

Uploaded Source

Built Distribution

pyopencga-2.12.3-py3-none-any.whl (87.4 kB view details)

Uploaded Python 3

File details

Details for the file pyopencga-2.12.3.tar.gz.

File metadata

  • Download URL: pyopencga-2.12.3.tar.gz
  • Upload date:
  • Size: 64.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.12

File hashes

Hashes for pyopencga-2.12.3.tar.gz
Algorithm Hash digest
SHA256 d86cb422b3e63e3ef945c74a727995621550dd45c1d8d1877a9a2ef161968752
MD5 d667878b76d268cfa4ce7e33965edd72
BLAKE2b-256 1d3cbb0bec39d7ddc1f3b645b6348238c78ba684eb62d2b536478b010be20927

See more details on using hashes here.

Provenance

File details

Details for the file pyopencga-2.12.3-py3-none-any.whl.

File metadata

  • Download URL: pyopencga-2.12.3-py3-none-any.whl
  • Upload date:
  • Size: 87.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.12

File hashes

Hashes for pyopencga-2.12.3-py3-none-any.whl
Algorithm Hash digest
SHA256 e4d0cee7a78ee0ea60c9f9ba53ef282692a6966d1ba5e3af38b6a541b67f8b8e
MD5 e298a614791e35ac6ed2422d3cb5a5ec
BLAKE2b-256 b28e417e158a16df30109c7bd95e91a2042ff1be851b5a13e229de887dac7093

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page