Encoding Clinical Data with HPO
We recommend that clinicians, genetic counselors, and other healthcare professionals who will be entering HPO terms as a part of clinical care consult this detailed protocol about how to choose optimal HPO terms in various clinical situations.
- Köhler S, Øien NC, et al (2019). Encoding Clinical Data with the Human Phenotype Ontology for Computational Differential Diagnostics. Curr Protoc Hum Genet. 2019 Sep;103(1):e92 PMID:31479590.
Exercise 1
This exercise may be difficult for those without medical training. We will extract a list of HPO terms from a published case report about an individual with X-linked Megalocornea.
- Han J, et al (2015) X-linked Megalocornea Associated with the Novel CHRDL1 Gene Mutation p.(Pro56Leu*8). Ophthalmic Genet;36:145-8 PMID:24073597.
Go to the clinical vignette in this article, and identify the phenotypic abnormalities. Use the HPO website to search for the corresponding HPO terms. Write down the list of terms.
Exercise 2
In practice, many people will use text mining approaches to help identify HPO terms in clinical texts. For this exercise, we will try another published case report:
- Brizola E, et al Variable clinical expression of Stickler Syndrome: A case report of a novel COL11A1 mutation. Mol Genet Genomic Med. 2020 Sep;8(9):e1353. PMID:32558342.
Try this tool to do the text mining.
doc2hpo has a nice online tutoral with more information about how to use the tool.
Wrap-up
In this module, you have practiced how to extract HPO terms from clinical texts. We have used published case reports to demonstrate the process. Analogous steps would be performed for real clinical data.
If you had trouble with any of the exercises, see the hints and answers.