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pronto : Python frontend to Ontologies

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Overview

Pronto is a python module to parse, create, browse and export ontologies from some popular formats. For now, obo and owl/xml are available, but more formats are to be added in the future (you can even add your own to work with the current API).

Installation

Installing with pip is the easiest:

pip install pronto          # if you have the admin rights
pip install pronto --user   # if you want to install it for only one user

There is also a conda recipe in the bioconda channel:

conda install -c bioconda pronto

If for some reason you do not like pip, you can also clone the repository and install it with the setup script (still requires setuptools):

git clone https://github.com/althonos/pronto
cd pronto
python setup.py install    # may also require admin rights

Usage

The Ontology class is the main entrypoint of pronto. It can be instantiated with a given ontology file (.owl, .ont or .obo) or from scratch, without any existing terms.

Open an ontology and get a term by accession:

import pronto
ont = pronto.Ontology('path/to/file.obo')
term = ont['REF:ACCESSION']

Display an ontology in obo format and in json format:

import pronto
ont = pronto.Ontology('https://net.path.should/work/too.owl')
print(ont.obo)
print(ont.json)

Merge two ontologies:

Example here uses the NMR controlled vocabulary and the HUPO-PSI MS controlled vocabulary

import pronto
nmr = pronto.Ontology('http://nmrml.org/cv/v1.1.0/nmrCV.owl')
ms  = pronto.Ontology('https://raw.githubusercontent.com/HUPO-PSI/psi-ms-CV/master/psi-ms.obo')
ms.merge(nmr)
>>> 'NMR:1000004' in ms
True
>>> ms.meta['coverage']
'Mass spectrometer output files and spectra interpretation'

Find ontology terms with children

import pronto
ont = pronto.Ontology('path/to/file.obo')
for term in ont:
    if term.children:
        print(term)

Get all the transitive children of an ontology term

import pronto
ont = pronto.Ontology('path/to/file.obo')
print(ont['RF:XXXXXXX'].rchildren())

Reference

If you wish to use this library in a scientific publication, please cite it ! (see the Zenodo record to get a DOI or a BibTEX record).

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this is a fork from the pronto repo

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