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Sunbursts for ontologies

Project description

Ontosunburst

Sunburst visualisation of an ontology representing classes of sets of metabolic objects

image image

Requirements

Mandatory

Python 3.10 recommended

Requirements from requirements.txt

  • numpy>=1.26.1
  • plotly>=5.17.0
  • scipy>=1.11.3
  • SPARQLWrapper>=2.0.0
  • pandas>=1.5.3

Optional

Need Apache Jena Fuseki SPARQL server for ChEBI and GO requests and their OWL files.

Installation

PyPI

pip install ontosunburst

Local

Inside the cloned repository :

pip install -r requirements.txt
pip install -e .

Set up Jena SPARQL server (optional : for ChEBI and GO)

Execute followed bash script to launch server.

ChEBI

#!/bin/bash

FUSEKI_PATH=/path/to/apache-jena-fuseki-x.x.x
CHEBI_PATH=/path/to//chebi_lite.owl

${FUSEKI_PATH}/fuseki-server --file=${CHEBI_PATH} /chebi

GO

#!/bin/bash

FUSEKI_PATH=/path/to/apache-jena-fuseki-x.x.x
GO_PATH=/path/to/go.owl

${FUSEKI_PATH}/fuseki-server --file=${GO_PATH} /go

Utilisation

Availabilities

5 Ontologies :

With local files :

  • MetaCyc (compounds, reactions, pathways)
  • EC (EC-numbers)
  • KEGG Ontology (modules, pathways, ko, ko_transporter, metabolite, metabolite_lipid)

With SPARQL server :

  • ChEBI (chebi roles)
  • Gene Ontology (<1000 go terms recommended in the interest set)

Personal ontology possible :

  • Define all the ontology classes relationship in a dictionary {class: [parent classes]}
  • Define the root : unique class with no parents

2 Analysis :

  • Topology (1 set + 1 optional reference set) : displays proportion (number of occurrences) representation of all classes
  • Enrichment (1 set + 1 reference set) : displays enrichment analysis significance of a set according to a reference set of metabolic objects

Documentation

View full documentation here : https://github.com/AuReMe/Ontosunburst/wiki

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