The visualization of Orphadata neurology phenotypes
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,...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-01-01
|
| Series: | Frontiers in Digital Health |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fdgth.2023.1064936/full |
| _version_ | 1811177006082031616 |
|---|---|
| author | Daniel B. Hier Daniel B. Hier Raghu Yelugam Michael D. Carrithers Donald C. Wunsch |
| author_facet | Daniel B. Hier Daniel B. Hier Raghu Yelugam Michael D. Carrithers Donald C. Wunsch |
| author_sort | Daniel B. Hier |
| collection | DOAJ |
| description | 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 Orphadata 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 superclasses. 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 Orphadata. Subsumption can collapse phenotype features into superclasses, phenotype lists can be vectorized, and phenotypes vectors can be visualized as heat maps and word clouds. |
| first_indexed | 2024-04-10T20:01:17Z |
| format | Article |
| id | doaj.art-453a2270e5364b1f824417e9474dfde0 |
| institution | Directory Open Access Journal |
| issn | 2673-253X |
| language | English |
| last_indexed | 2024-04-10T20:01:17Z |
| publishDate | 2023-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Digital Health |
| spelling | doaj.art-453a2270e5364b1f824417e9474dfde02023-01-27T04:51:43ZengFrontiers Media S.A.Frontiers in Digital Health2673-253X2023-01-01510.3389/fdgth.2023.10649361064936The visualization of Orphadata neurology phenotypesDaniel B. Hier0Daniel B. Hier1Raghu Yelugam2Michael D. Carrithers3Donald C. Wunsch4Applied Computational Intelligence Laboratory, Department of Electrical & Computer Engineering, Missouri University of Science & Technology, Rolla, MO, United StatesDepartment of Neurology and Rehabilitation, University of Illinois at Chicago, Chicago, IL, United StatesApplied Computational Intelligence Laboratory, Department of Electrical & Computer Engineering, Missouri University of Science & Technology, Rolla, MO, United StatesDepartment of Neurology and Rehabilitation, University of Illinois at Chicago, Chicago, IL, United StatesNational Institute of Diabetes and Digestive and Kidney Diseases, Liver Diseases Branch, Bethesda, MD, United StatesDisease 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 Orphadata 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 superclasses. 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 Orphadata. Subsumption can collapse phenotype features into superclasses, phenotype lists can be vectorized, and phenotypes vectors can be visualized as heat maps and word clouds.https://www.frontiersin.org/articles/10.3389/fdgth.2023.1064936/fullneurologyphenotypingsubsumptionontologyvisualizationheat maps |
| spellingShingle | Daniel B. Hier Daniel B. Hier Raghu Yelugam Michael D. Carrithers Donald C. Wunsch The visualization of Orphadata neurology phenotypes Frontiers in Digital Health neurology phenotyping subsumption ontology visualization heat maps |
| title | The visualization of Orphadata neurology phenotypes |
| title_full | The visualization of Orphadata neurology phenotypes |
| title_fullStr | The visualization of Orphadata neurology phenotypes |
| title_full_unstemmed | The visualization of Orphadata neurology phenotypes |
| title_short | The visualization of Orphadata neurology phenotypes |
| title_sort | visualization of orphadata neurology phenotypes |
| topic | neurology phenotyping subsumption ontology visualization heat maps |
| url | https://www.frontiersin.org/articles/10.3389/fdgth.2023.1064936/full |
| work_keys_str_mv | AT danielbhier thevisualizationoforphadataneurologyphenotypes AT danielbhier thevisualizationoforphadataneurologyphenotypes AT raghuyelugam thevisualizationoforphadataneurologyphenotypes AT michaeldcarrithers thevisualizationoforphadataneurologyphenotypes AT donaldcwunsch thevisualizationoforphadataneurologyphenotypes AT danielbhier visualizationoforphadataneurologyphenotypes AT danielbhier visualizationoforphadataneurologyphenotypes AT raghuyelugam visualizationoforphadataneurologyphenotypes AT michaeldcarrithers visualizationoforphadataneurologyphenotypes AT donaldcwunsch visualizationoforphadataneurologyphenotypes |