Rojano, ElenaCórdoba-Caballero, JoséJabato, Fernando M.Gallego, DianaSerrano, MercedesPérez, BelénParés-Aguilar, ÁlvaroPerkins, James R.Ranea, Juan A G.Seoane-Zonjic, Pedro2022-08-222022-08-222021-07-27Rojano E, Córdoba-Caballero J, Jabato FM, Gallego D, Serrano M, Pérez B, et al. Evaluating, Filtering and Clustering Genetic Disease Cohorts Based on Human Phenotype Ontology Data with Cohort Analyzer. J Pers Med. 2021 Jul 27;11(8):730http://hdl.handle.net/10668/3924Exhaustive 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.enAtribución 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/Genetic diseasesCohort analyzerHuman phenotype ontologyCluster analysisPhenotype quality assessmentEnfermedades genéticas congénitasOntología de genesAnálisis por gruposFenotipoGarantía de la calidad de atención de saludMedical Subject Headings::Organisms::Eukaryota::Animals::Chordata::Vertebrates::Mammals::Primates::Haplorhini::Catarrhini::Hominidae::HumansMedical Subject Headings::Information Science::Information Science::Systems Analysis::WorkflowMedical Subject Headings::Phenomena and Processes::Genetic Phenomena::PhenotypeMedical Subject Headings::Disciplines and Occupations::Natural Science Disciplines::Biological Science Disciplines::Biology::Genetics::GenomicsMedical Subject Headings::Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Statistics as Topic::Cluster Analysisresearch article34442375Acceso abierto10.3390/jpm110807302075-4426PMC8398478