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Title: Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research [v2; ref status: indexed, http://f1000r.es/2td]

Journal Article · · F1000Research
 [1];  [2];  [3];  [2];  [4];  [3];  [5];  [6];  [7];  [4];  [8];  [4]
  1. Charité-Universitatsmedizin Berlin (Germany). Inst. for Medical and Human Genetics; Charité-Universitatsmedizin Berlin (Germany). Berlin-Brandenberg Center for Regenerative Therapies (BCRT)
  2. Charité-Universitatsmedizin Berlin (Germany). Inst. for Medical and Human Genetics
  3. Univ. of Oregon, Eugene, OR (United States). Inst. of Neuroscience, Zebrafish Facility (ZFIN)
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  5. Univ. of Aberystwyth (United Kingdom). Dept. of Computer Science
  6. Univ. of Cambridge (United Kingdom). Dept. of Genetics
  7. Wellcome Trust Sanger Inst., Cambridge (United Kingdom)
  8. Charité-Universitatsmedizin Berlin (Germany). Inst. for Medical and Human Genetics; Charité-Universitatsmedizin Berlin (Germany). Berlin-Brandenberg Center for Regenerative Therapies (BCRT); Max Planck Inst. for Molecular Genetics, Berlin (Germany)

Phenotype analyses, e.g. investigating metabolic processes, tissue formation, or organism behavior, are an important element of most biological and medical research activities. Biomedical researchers are making increased use of ontological standards and methods to capture the results of such analyses, with one focus being the comparison and analysis of phenotype information between species. We have generated a cross-species phenotype ontology for human, mouse and zebrafish that contains classes from the Human Phenotype Ontology, Mammalian Phenotype Ontology, and generated classes for zebrafish phenotypes. We also provide up-to-date annotation data connecting human genes to phenotype classes from the generated ontology. We have included the data generation pipeline into our continuous integration system ensuring stable and up-to-date releases. This article describes the data generation process and is intended to help interested researchers access both the phenotype annotation data and the associated cross-species phenotype ontology. The resource described here can be used in sophisticated semantic similarity and gene set enrichment analyses for phenotype data across species. The stable releases of this resource can be obtained fromhttp://purl.obolibrary.org/obo/hp/uberpheno/.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division; USDOE Office of Science (SC), Basic Energy Sciences (BES); German Research Foundation (DFG); Bundesministerium für Bildung und Forschung (BMBF); National Institutes of Health (NIH)
Grant/Contract Number:
AC02-05CH11231; DFG RO 2005/4-1; HG000330; U41-HG002659; R01-HG004838; R24-OD011883
OSTI ID:
1629554
Journal Information:
F1000Research, Vol. 2; ISSN 2046-1402
Publisher:
F1000ResearchCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (42)

Exome sequencing for gene discovery in lethal fetal disorders - harnessing the value of extreme phenotypes: Gene discovery in lethal fetal phenotypes journal August 2014
The flora phenotype ontology (FLOPO): tool for integrating morphological traits and phenotypes of vascular plants journal November 2016
Neuroinformatic analyses of common and distinct genetic components associated with major neuropsychiatric disorders journal November 2014
Cross-organism analysis using InterMine: cross-organism analysis using InterMine journal July 2015
Use of Model Organism and Disease Databases to Support Matchmaking for Human Disease Gene Discovery journal September 2015
Disease insights through cross-species phenotype comparisons journal June 2015
Identification of sequence variants influencing immunoglobulin levels journal June 2017
Next-generation diagnostics and disease-gene discovery with the Exomiser journal November 2015
Xrare: a machine learning method jointly modeling phenotypes and genetic evidence for rare disease diagnosis journal January 2019
PathoPhenoDB, linking human pathogens to their phenotypes in support of infectious disease research journal June 2019
Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies journal March 2019
Drug-induced adverse events prediction with the LINCS L1000 data journal April 2016
PhenomeScape: a cytoscape app to identify differentially regulated sub-networks using known disease associations journal August 2016
Formal axioms in biomedical ontologies improve analysis and interpretation of associated data journal December 2019
Ontology based text mining of gene-phenotype associations: application to candidate gene prediction journal January 2019
The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data journal November 2013
The Human Phenotype Ontology in 2017 journal November 2016
The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species journal November 2019
A dominant gain-of-function mutation in universal tyrosine kinase SRC causes thrombocytopenia, myelofibrosis, bleeding, and bone pathologies journal March 2016
Aber-OWL: a framework for ontology-based data access in biology journal January 2015
Deletions of chromosomal regulatory boundaries are associated with congenital disease journal September 2014
Finding Our Way through Phenotypes journal January 2015
Phenotype Ontologies and Cross-Species Analysis for Translational Research journal April 2014
The digital revolution in phenotyping text January 2016
Integrating phenotype ontologies with PhenomeNET collection January 2017
DeepPVP: phenotype-based prioritization of causative variants using deep learning. text January 2019
The anatomy of phenotype ontologies: principles, properties and applications text January 2017
The anatomy of phenotype ontologies: principles, properties and applications journal April 2017
The Monarch Initiative: an integrative data and analytic platform connecting phenotypes to genotypes across species journal November 2016
Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies posted_content July 2018
The digital revolution in phenotyping journal September 2015
DeepPVP: phenotype-based prioritization of causative variants using deep learning posted_content May 2018
Integrating phenotype ontologies with PhenomeNET. text January 2017
The Human Phenotype Ontology in 2017. text January 2017
Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies. text January 2019
PathoPhenoDB, linking human pathogens to their phenotypes in support of infectious disease research. text January 2019
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GeneTIER: prioritization of candidate disease genes using tissue-specific gene expression profiles journal April 2015
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Automatic concept recognition using the Human Phenotype Ontology reference and test suite corpora journal January 2015
Representing glycophenotypes: semantic unification of glycobiology resources for disease discovery journal January 2019
The cellular microscopy phenotype ontology journal May 2016

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