Jian Yang1,2, Cong Dong1,2, Huilong Duan2, Qiang Shu1, Haomin Li3. 1. The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Binsheng Road 3333#, Hangzhou, Zhejiang, 310052, China. 2. The College of Biomedical Engineering and Instrument Science, Zhejiang University, Zhejiang, China. 3. The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Binsheng Road 3333#, Hangzhou, Zhejiang, 310052, China. hmli@zju.edu.cn.
Abstract
BACKGROUND: The complexity of the phenotypic characteristics and molecular bases of many rare human genetic diseases makes the diagnosis of such diseases a challenge for clinicians. A map for visualizing, locating and navigating rare diseases based on similarity will help clinicians and researchers understand and easily explore these diseases. METHODS: A distance matrix of rare diseases included in Orphanet was measured by calculating the quantitative distance among phenotypes and pathogenic genes based on Human Phenotype Ontology (HPO) and Gene Ontology (GO), and each disease was mapped into Euclidean space. A rare disease map, enhanced by clustering classes and disease information, was developed based on ECharts. RESULTS: A rare disease map called RDmap was published at http://rdmap.nbscn.org . Total 3287 rare diseases are included in the phenotype-based map, and 3789 rare genetic diseases are included in the gene-based map; 1718 overlapping diseases are connected between two maps. RDmap works similarly to the widely used Google Map service and supports zooming and panning. The phenotype similarity base disease location function performed better than traditional keyword searches in an in silico evaluation, and 20 published cases of rare diseases also demonstrated that RDmap can assist clinicians in seeking the rare disease diagnosis. CONCLUSION: RDmap is the first user-interactive map-style rare disease knowledgebase. It will help clinicians and researchers explore the increasingly complicated realm of rare genetic diseases.
BACKGROUND: The complexity of the phenotypic characteristics and molecular bases of many rare humangenetic diseases makes the diagnosis of such diseases a challenge for clinicians. A map for visualizing, locating and navigating rare diseases based on similarity will help clinicians and researchers understand and easily explore these diseases. METHODS: A distance matrix of rare diseases included in Orphanet was measured by calculating the quantitative distance among phenotypes and pathogenic genes based on Human Phenotype Ontology (HPO) and Gene Ontology (GO), and each disease was mapped into Euclidean space. A rare disease map, enhanced by clustering classes and disease information, was developed based on ECharts. RESULTS: A rare disease map called RDmap was published at http://rdmap.nbscn.org . Total 3287 rare diseases are included in the phenotype-based map, and 3789 rare genetic diseases are included in the gene-based map; 1718 overlapping diseases are connected between two maps. RDmap works similarly to the widely used Google Map service and supports zooming and panning. The phenotype similarity base disease location function performed better than traditional keyword searches in an in silico evaluation, and 20 published cases of rare diseases also demonstrated that RDmap can assist clinicians in seeking the rare disease diagnosis. CONCLUSION: RDmap is the first user-interactive map-style rare disease knowledgebase. It will help clinicians and researchers explore the increasingly complicated realm of rare genetic diseases.
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