Evaluating, Filtering and Clustering Genetic Disease Cohorts Based on Human Phenotype Ontology Data with Cohort Analyzer
| Autor: | Pedro Seoane-Zonjic, Álvaro Parés-Aguilar, Belén Pérez, Elena Rojano, Fernando M. Jabato, Mercedes Serrano, James R. Perkins, José Córdoba-Caballero, Juan A. G. Ranea, D. Gallego |
|---|---|
| Přispěvatelé: | [Rojano,E, Córdoba-Caballero,J, Parés-Aguilar,Á, Perkins,JR, Ranea,JAG, Seoane-Zonjic,P] Department of Molecular Biology and Biochemistry, University of Málaga, Málaga, Spain. [Rojano,E, Jabato,FM, Seoane-Zonjic,P] Institute of Biomedical Research in Málaga (IBIMA), Málaga, Spain. [Jabato,FM] Supercomputation and Bioinformatics (SCBI), University of Malaga, Malaga, Spain. [Jabato,FM] LifeWatch-ERIC, Seville, Spain. [Gallego,D, Serrano,M, Pérez,B, Seoane-Zonjic,P] Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), [Madrid, Málaga, Barcelona], Instituto de Salud Carlos III, Madrid, Spain. [Gallego,D, Pérez,B] Centro de Diagnóstico de Enfermedades Moleculares, Centro de Biología Molecular-SO UAM-CSIC, Universidad Autónoma de Madrid, Madrid, Spain. [Gallego,D, Pérez,B] Instituto de Investigación Sanitaria idiPAZ, Madrid, Spain. [Serrano,M] Neuropediatric Department, Institut de Recerca Hospital Sant Joan de Déu, Barcelona, Spain., This work was supported by The Spanish Ministry of Economy and Competitiveness with European Regional Development Fund [PID2019-108096RB-C21], the Andalusian Government with European Regional Development Fund [UMA18-FEDERJA-102 and PAIDI 2020:PY20-00372], biomedicine research project [PI-0075-2017] (Fundación Progreso y Salud), the Carlos III Health Institute [PI19/01155], the Madrid Government [B2017/BMD-3721], the Ramón Areces foundation for rare disease investigation (National call for research on life and material sciences, XIX edition). We thank the patients and patients’ families for their collaboration and consent. PMM2-CDG research is supported by national grants from the National Plan on I+D+I, cofinanced by ISCIII (Subdirección General de Evaluación y Fomento de la Investigación Sanitaria) and FEDER (Fondo Europeo de Desarrollo Regional) [PI14/00021, PI17/00101 ]. Dr. Serrano’s research work is supported by a grant from the Generalitat de Catalunya [PERIS SLT008/18/00194]. The CIBERER is an initiative from the Carlos III Health Institute (Instituto de Salud Carlos III)., Ministerio de Economía y Competitividad (España), Junta de Andalucía, Instituto de Salud Carlos III, Comunidad de Madrid, Fundación Ramón Areces, Generalitat de Catalunya, Centro de Investigación Biomédica en Red Enfermedades Raras (España) |
| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
Phenomena and Processes::Genetic Phenomena::Phenotype [Medical Subject Headings] Ontología de genes Genomic data Análisis por grupos Medicine (miscellaneous) Computational biology Disease Phenotype quality assessment Biology Analytical Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Statistics as Topic::Cluster Analysis [Medical Subject Headings] Cohort analyzer Article Organisms::Eukaryota::Animals::Chordata::Vertebrates::Mammals::Primates::Haplorhini::Catarrhini::Hominidae::Humans [Medical Subject Headings] 03 medical and health sciences Cluster analysis 0302 clinical medicine Human Phenotype Ontology Garantía de la calidad de atención de salud Information Science::Information Science::Systems Analysis::Workflow [Medical Subject Headings] Enfermedades genéticas congénitas business.industry Human phenotype ontology 030104 developmental biology Cohort Medicine Disciplines and Occupations::Natural Science Disciplines::Biological Science Disciplines::Biology::Genetics::Genomics [Medical Subject Headings] Personalized medicine business Fenotipo 030217 neurology & neurosurgery Genetic diseases |
| Zdroj: | Journal of Personalized Medicine Journal of Personalized Medicine, Vol 11, Iss 730, p 730 (2021) Volume 11 Issue 8 Digital.CSIC. Repositorio Institucional del CSIC instname |
| ISSN: | 2075-4426 |
| DOI: | 10.3390/jpm11080730 |
| Popis: | Exhaustive and comprehensive analysis of pathological traits is essential to understanding genetic diseases, performing precise diagnosis and prescribing personalized treatments. It is particularly important for disease cohorts, as thoroughly detailed phenotypic profiles allow patients to be compared and contrasted. However, many disease cohorts contain patients that have been ascribed low numbers of very general and relatively uninformative phenotypes. We present Cohort Analyzer, a tool that measures the phenotyping quality of patient cohorts. It calculates multiple statistics to give a general overview of the cohort status in terms of the depth and breadth of phenotyping, allowing us to detect less well-phenotyped patients for re-examining or excluding from further analyses. In addition, it performs clustering analysis to find subgroups of patients that share similar phenotypic profiles. We used it to analyse three cohorts of genetic diseases patients with very different properties. We found that cohorts with the most specific and complete phenotypic characterization give more potential insights into the disease than those that were less deeply characterised by forming more informative clusters. For two of the cohorts, we also analysed genomic data related to the patients, and linked the genomic data to the patient-subgroups by mapping shared variants to genes and functions. The work highlights the need for improved phenotyping in this era of personalized medicine. The tool itself is freely available alongside a workflow to allow the analyses shown in this work to be applied to other datasets. The Spanish Ministry of Economy and Competitiveness with European Regional Development Fund [PID2019-108096RB-C21]; the Andalusian Government with European Regional Development Fund [UMA18-FEDERJA-102 and PAIDI 2020:PY20-00372]; biomedicine research project [PI-0075-2017] (Fundación Progreso y Salud); the Carlos III Health Institute [PI19/01155]; the Madrid Government [B2017/BMD-3721]; the Ramón Areces and foundation Generalitat de Catalunya [PERIS LT008/18/00194]. The CIBERER is an initiative from the Carlos III Health Institute (Instituto de Salud Carlos III) |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|