The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease

Groza, Tudor; Köhler, Sebastian; Moldenhauer, Dawid; Vasilevsky, Nicole; Baynam, Gareth; Żemojtel, Tomasz; Schriml, Lynn M.; Kibbe, Warren A.; Schofield, Paul N.; Beck, Tim; Vasant, Drashtti; Brookes, Anthony J.; Zankl, Andreas; Washington, Nicole; Mungall, Christopher J.; Lewis, Suzanna; Haendel, Melissa; Parkinson, Helen; Robinson, Peter N.

doi:10.1016/j.ajhg.2015.05.020

Cited by 202 publications

(156 citation statements)

References 85 publications

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“…The Mouse Genome Informatics database enables queries for humanmouse disease and Mammalian Phenotype Ontology (MPO) connections using gene symbols as an input (www.informatics.jax.org/humanDisease.shtml). The Human Phenotype Ontology (HPO) project (60) also provides gene-to-phenotype mappings, which can be used in a similar manner (http://human-phenotype-ontology.org). HPO plays a key role in the Monarch Initiative (61), which provides tools for genotypephenotype analysis across broad areas of disease (https://monarchinitiative.org).…”

Section: Knowledge-driven Variant Prioritizationmentioning

confidence: 99%

A Practical Guide To Filtering and Prioritizing Genetic Variants

Dashti

Gamieldien

2017

BioTechniques

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Next-generation sequencing (NGS) of whole genomes and exomes is a powerful tool in biomedical research and clinical diagnostics. However, the vast amount of data produced by NGS introduces new challenges and opportunities, many of which require novel computational and theoretical approaches when it comes to identifying the causal variant(s) for a disease of interest. While workflows and associated software to process raw data and produce high-confidence variant calls have significantly improved, filtering tens of thousands of candidates to identify a subset relevant to a specific study is still a complex exercise best left to bioinformaticists. However, as this prioritization procedure requires biological/biomedical reasoning, biologists and clinicians are increasingly motivated to handle the task themselves. Here, we describe a set of guidelines, tools, and online resources that can be used to identify functional variants from whole-genome and whole-exome variant calls and then prioritize these variants with potential associations to phenotypes of interest. Insights gained from a recently published analysis of protein-coding gene variation in >60,000 humans by the Exome Aggregation Consortium (ExAC) are also taken into account.

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Section: Knowledge-driven Variant Prioritizationmentioning

confidence: 99%

A Practical Guide To Filtering and Prioritizing Genetic Variants

Dashti

Gamieldien

2017

BioTechniques

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“…Data standardization The establishment of a unified registry system first requires the development of unified standards, and especially data transmission standards, terminology and ontology, and research protocols (22). The level of diagnosis and treatment at domestic hospitals in China varies more widely than that in other countries, resulting in substantial problems with inconsistent, non-standard diagnosis and treatment.…”

Section: Challenges To the Promotion Of Rare Diseases Research In Chinamentioning

confidence: 99%

Innovative measures to combat rare diseases in China: The national rare diseases registry system, larger-scale clinical cohort studies, and studies in combination with precision medicine research

Song

et al. 2017

IRDR

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“…Existing descriptions of phenotypes and their relationships to genomic variations are all-too-frequently provided in community-specific formats, which lack the details and computational meaning needed for integration. Although we have made some progress with natural language approaches to extracting key details (Groza et al 2015), expensive manual curation is still necessary.…”

Section: A Common Conceptual Frameworkmentioning

confidence: 99%

Navigating the Phenotype Frontier: The Monarch Initiative

et al. 2016

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The principles of genetics apply across the entire tree of life. At the cellular level we share biological mechanisms with species from which we diverged millions, even billions of years ago. We can exploit this common ancestry to learn about health and disease, by analyzing DNA and protein sequences, but also through the observable outcomes of genetic differences, i.e. phenotypes. To solve challenging disease problems we need to unify the heterogeneous data that relates genomics to disease traits. Without a big-picture view of phenotypic data, many questions in genetics are difficult or impossible to answer. The Monarch Initiative (https://monarchinitiative.org) provides tools for genotype-phenotype analysis, genomic diagnostics, and precision medicine across broad areas of disease.

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The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease

Cited by 202 publications

References 85 publications

A Practical Guide To Filtering and Prioritizing Genetic Variants

A Practical Guide To Filtering and Prioritizing Genetic Variants

Innovative measures to combat rare diseases in China: The national rare diseases registry system, larger-scale clinical cohort studies, and studies in combination with precision medicine research

Navigating the Phenotype Frontier: The Monarch Initiative

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