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

Python 3.10 recommended

Requirements from requirements.txt

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

Need Apache Jena Fuseki SPARQL server to generate your own CHEBI and GO ontology input files

• Download Apache Jena Fuseki : https://jena.apache.org/download/index.cgi
• Download ChEBI ontology : https://ftp.ebi.ac.uk/pub/databases/chebi/ontology/ (chebi.owl or chebi_lite.owl)
• Download GO ontology : https://geneontology.org/docs/download-ontology/ (go-basic.owl)

pip install ontosunburst

Inside the cloned repository :

pip install -e .

• Metacyc classes v26.0 (compounds, reactions, pathways): metacyc
• Enzyme commission numbers v05 feb 2025 (EC-numbers): ec
• Kegg classes v113.0 (modules, pathways, ko, ko_transporter, metabolite, metabolite_lipid): kegg
• Gene Ontology Cellular Components classes v06 feb 2025 : go_cc
• Gene Ontology Molecular Functions classes v06 feb 2025 : go_mf
• Gene Ontology Biological Process classes v06 feb 2025 : go_bp
• Gene Ontology classes (Fusion of 3) v06 feb 2025 : go
• ChEBI classes v239: chebi
• ChEBI roles: v239: chebi_r

Personal ontology possible :

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

• 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

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

• plotly: Plotly Technologies Inc. Collaborative data science. Montréal, QC, 2015. https://plot.ly.

• MetaCyc:

  • Caspi, R., Billington, R., Keseler, I. M., Kothari, A., Krummenacker, M., Midford, P. E., Ong, W. K., Paley, S., Subhraveti, P., & Karp, P. D. (2020). The MetaCyc database of metabolic pathways and enzymes - a 2019 update. Nucleic acids research, 48(D1), D445–D453. https://doi.org/10.1093/nar/gkz862
  • Ron Caspi, Kate Dreher, Peter D. Karp, The challenge of constructing, classifying, and representing metabolic pathways, FEMS Microbiology Letters, Volume 345, Issue 2, August 2013, Pages 85–93, https://doi.org/10.1111/1574-6968.12194
  • Karp, P.D., Caspi, R. A survey of metabolic databases emphasizing the MetaCyc family. Arch Toxicol 85, 1015–1033 (2011). https://doi.org/10.1007/s00204-011-0705-2

• KEGG:

  • Minoru Kanehisa, Miho Furumichi, Yoko Sato, Yuriko Matsuura, Mari Ishiguro-Watanabe, KEGG: biological systems database as a model of the real world, Nucleic Acids Research, Volume 53, Issue D1, 6 January 2025, Pages D672–D677, https://doi.org/10.1093/nar/gkae909

• EC:

  • Amos Bairoch, The ENZYME database in 2000, Nucleic Acids Research, Volume 28, Issue 1, 1 January 2000, Pages 304–305, https://doi.org/10.1093/nar/28.1.304

• ChEBI:

  • Janna Hastings, Gareth Owen, Adriano Dekker, Marcus Ennis, Namrata Kale, Venkatesh Muthukrishnan, Steve Turner, Neil Swainston, Pedro Mendes, Christoph Steinbeck, ChEBI in 2016: Improved services and an expanding collection of metabolites, Nucleic Acids Research, Volume 44, Issue D1, 4 January 2016, Pages D1214–D1219, https://doi.org/10.1093/nar/gkv1031

• GO:

  • The Gene Ontology Consortium , Suzi A Aleksander, James Balhoff, Seth Carbon, J Michael Cherry, Harold J Drabkin, Dustin Ebert, Marc Feuermann, Pascale Gaudet, Nomi L Harris, David P Hill, Raymond Lee, Huaiyu Mi, Sierra Moxon, Christopher J Mungall, Anushya Muruganugan, Tremayne Mushayahama, Paul W Sternberg, Paul D Thomas, Kimberly Van Auken, Jolene Ramsey, Deborah A Siegele, Rex L Chisholm, Petra Fey, Maria Cristina Aspromonte, Maria Victoria Nugnes, Federica Quaglia, Silvio Tosatto, Michelle Giglio, Suvarna Nadendla, Giulia Antonazzo, Helen Attrill, Gil dos Santos, Steven Marygold, Victor Strelets, Christopher J Tabone, Jim Thurmond, Pinglei Zhou, Saadullah H Ahmed, Praoparn Asanitthong, Diana Luna Buitrago, Meltem N Erdol, Matthew C Gage, Mohamed Ali Kadhum, Kan Yan Chloe Li, Miao Long, Aleksandra Michalak, Angeline Pesala, Armalya Pritazahra, Shirin C C Saverimuttu, Renzhi Su, Kate E Thurlow, Ruth C Lovering, Colin Logie, Snezhana Oliferenko, Judith Blake, Karen Christie, Lori Corbani, Mary E Dolan, Harold J Drabkin, David P Hill, Li Ni, Dmitry Sitnikov, Cynthia Smith, Alayne Cuzick, James Seager, Laurel Cooper, Justin Elser, Pankaj Jaiswal, Parul Gupta, Pankaj Jaiswal, Sushma Naithani, Manuel Lera-Ramirez, Kim Rutherford, Valerie Wood, Jeffrey L De Pons, Melinda R Dwinell, G Thomas Hayman, Mary L Kaldunski, Anne E Kwitek, Stanley J F Laulederkind, Marek A Tutaj, Mahima Vedi, Shur-Jen Wang, Peter D’Eustachio, Lucila Aimo, Kristian Axelsen, Alan Bridge, Nevila Hyka-Nouspikel, Anne Morgat, Suzi A Aleksander, J Michael Cherry, Stacia R Engel, Kalpana Karra, Stuart R Miyasato, Robert S Nash, Marek S Skrzypek, Shuai Weng, Edith D Wong, Erika Bakker, Tanya Z Berardini, Leonore Reiser, Andrea Auchincloss, Kristian Axelsen, Ghislaine Argoud-Puy, Marie-Claude Blatter, Emmanuel Boutet, Lionel Breuza, Alan Bridge, Cristina Casals-Casas, Elisabeth Coudert, Anne Estreicher, Maria Livia Famiglietti, Marc Feuermann, Arnaud Gos, Nadine Gruaz-Gumowski, Chantal Hulo, Nevila Hyka-Nouspikel, Florence Jungo, Philippe Le Mercier, Damien Lieberherr, Patrick Masson, Anne Morgat, Ivo Pedruzzi, Lucille Pourcel, Sylvain Poux, Catherine Rivoire, Shyamala Sundaram, Alex Bateman, Emily Bowler-Barnett, Hema Bye-A-Jee, Paul Denny, Alexandr Ignatchenko, Rizwan Ishtiaq, Antonia Lock, Yvonne Lussi, Michele Magrane, Maria J Martin, Sandra Orchard, Pedro Raposo, Elena Speretta, Nidhi Tyagi, Kate Warner, Rossana Zaru, Alexander D Diehl, Raymond Lee, Juancarlos Chan, Stavros Diamantakis, Daniela Raciti, Magdalena Zarowiecki, Malcolm Fisher, Christina James-Zorn, Virgilio Ponferrada, Aaron Zorn, Sridhar Ramachandran, Leyla Ruzicka, Monte Westerfield, The Gene Ontology knowledgebase in 2023, Genetics, Volume 224, Issue 1, May 2023, iyad031, https://doi.org/10.1093/genetics/iyad031
  • Ashburner, M., Ball, C., Blake, J. et al. Gene Ontology: tool for the unification of biology. Nat Genet 25, 25–29 (2000). https://doi.org/10.1038/75556