Metadata-Version: 2.0
Name: ontobio
Version: 0.1.2
Summary: Library for working with OBO Library Ontologies and associations
Home-page: https://github.com/biolink-api/ontobio
Author: Chris Mungall
Author-email: cmungall@gmail.com
License: BSD
Keywords: ontology graph obo owl sparql networkx network
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Dist: cachier
Requires-Dist: networkx
Requires-Dist: prefixcommons
Requires-Dist: pysolr
Requires-Dist: pyyaml
Requires-Dist: requests
Requires-Dist: scipy
Requires-Dist: sparqlwrapper
Provides-Extra: dev
Requires-Dist: plotly; extra == 'dev'
Provides-Extra: test
Requires-Dist: pytest; extra == 'test'

ontobio - a python API for working with ontology graphs
=======================================================

This module provides objects and utility methods for working with
ontologies and associations of entities (genes, variants, etc) to
ontology classes.

The ontologies and associations can either be local files or provided by
remote services (currently the OntoBee SPARQL service for ontologies and
a Monarch or GO Golr service for associations).

Ontologies
==========

There are two ways of initiating an ontology object:

-  via a local obo-json file
-  via remote connections to OBO PURLs
-  via remote query to a SPARQL service (currently ontobee, but soon
   others)

Persistent caching is used (currently cachier) to avoid repeated
expensive I/O connections

This is handled via the `ontol\_manager.py <ontobio/ontol_manager.py>`__
module. This creates an ontology object (see
`ontol.py <ontobio/ontol.py>`__ ).

Note that object modeling is lightweight - we use the python networkx
package for representing the basic graph portion of an ontology. See
also the `obographs <https://github.com/geneontology/obographs>`__ spec.

Associations
============

See the ontobio.golr backage

Command Line Usage
==================

Initial Setup
-------------

::

    export PATH $HOME/repos/bioink-api/ontobio/bin
    ogr -h

Note you need to be connected to a network

Note: command line interface may change

Connecting to ontologies
------------------------

Specify an ontology with the ``-r`` option. this will always be the OBO
name, for example ``go``, ``cl``, ``mp``, etc

-  ``-r go`` connect to GO via default method (currently SPARQL)
-  ``-r obo:go`` connect to GO via download and cache of ontology from
   PURL
-  ``-r /users/my/my-ontologies/go.json`` use local download of ontology

In the following we assume default method, but can be substituted.

Ancestors queries
-----------------

List all ancestors:

::

    ogr -r cl neuron

Show ancestors as tree, following only subclass:

::

    ogr -r cl -p subClassOf -t tree neuron

generates:

::

         % GO:0005623 ! cell
          % CL:0000003 ! native cell
           % CL:0000255 ! eukaryotic cell
            % CL:0000548 ! animal cell
             % CL:0002319 ! neural cell
              % CL:0000540 ! neuron * 
           % CL:0002371 ! somatic cell
            % CL:0002319 ! neural cell
             % CL:0000540 ! neuron * 

Descendants of neuron, parts and subtypes

::

    ogr -r cl -p subClassOf -p BFO:0000050 -t tree -d d neuron

Descendants and ancestors of neuron, parts and subtypes

::

    ogr -r cl -p subClassOf -p BFO:0000050 -t tree -d du neuron

All ancestors of all classes 2 levels down from subclass-roots within
CL:

::

    ogr -r cl -P CL -p subClassOf -t tree -d u -L 2

Visualization using obographviz
-------------------------------

Requires: https://www.npmjs.com/package/obographviz

Add og2dot.js to path

::

    ogr -p subClassOf BFO:0000050 -r go -t png   a nucleus

This proceeds by:

1. Using the python ontobio library to extract a networkx subgraph
   around the specified node
2. Write as obographs-json
3. Calls og2dot.js

Output:

.. figure:: https://github.com/biolink/biolink-api/raw/master/ontobio/docs/nucleus.png
   :alt: img

   img
Search
------

List exact matches to neuron

::

    ogr -r cl neuron

Terms starting with neuron, SQL style

::

    ogr -r cl neuron%

Terms starting with neuron, regex (equivalent to above)

::

    ogr -r cl -s r ^neuron

Terms ending with neuron

::

    ogr -r cl -s r neuron$

Terms containing the string neuron

::

    ogr -r cl -s r neuron

Note: any of the above can be fed into other renderers, e.g. trees,
graphs

E.g. terms containing neuron, to obo

::

    ogr -r cl %neuron% -t obo

E.g. terms ending neuron, to tree

::

    ogr -r cl %neuron -t tree



