Abstract

Disease Phenotypes Are Characterized by Signs (What a Physician Observes during the Examination of a Patient) and Symptoms (The Complaints of a Patient to a Physician). Large Repositories of Disease Phenotypes Are Accessible through the Online Mendelian Inheritance of Man, Human Phenotype Ontology, and Orpha data Initiatives. Many of the Diseases in These Datasets Are Neurologic. for Each Repository, the Phenotype of Neurologic Disease is Represented as a List of Concepts of Variable Length Where the Concepts Are Selected from a Restricted Ontology. Visualizations of These Concept Lists Are Not Provided. We Address This Limitation by using Subsumption to Reduce the Number of Descriptive Features from 2,946 Classes into Thirty Super classes. Phenotype Feature Lists of Variable Lengths Were Converted into Fixed-Length Vectors. Phenotype Vectors Were Aggregated into Matrices and Visualized as Heat Maps that Allowed Side-By-Side Disease Comparisons. Individual Diseases (Representing a Row in the Matrix) Were Visualized as Word Clouds. We Illustrate the Utility of This Approach by Visualizing the Neuro-Phenotypes of 32 Dystonic Diseases from Orpha data. Subsumption Can Collapse Phenotype Features into Super classes, Phenotype Lists Can Be Vectorized, and Phenotypes Vectors Can Be Visualized as Heat Maps and Word Clouds.

Department(s)

Electrical and Computer Engineering

Comments

U.S. Department of Veterans Affairs, Grant None

Keywords and Phrases

feature reduction; heat maps; neurology; ontology; phenotyping; subsumption; visualization

International Standard Serial Number (ISSN)

2673-253X

Document Type

Article - Journal

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2023 The Authors, All rights reserved.

Creative Commons Licensing

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Publication Date

27 Jan 2023

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