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Title: The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species

Abstract

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

Authors:
ORCiD logo [1];  [2];  [3];  [4];  [2];  [5];  [1];  [1]; ORCiD logo [5];  [3]; ORCiD logo [6];  [7];  [8];  [3];  [9];  [2];  [3];  [10];  [11];  [12] more »;  [13];  [2];  [5];  [14];  [15];  [5];  [16];  [17];  [18];  [19];  [2]; ORCiD logo [4];  [1];  [2];  [20];  [4];  [17];  [1];  [3];  [2];  [21];  [22];  [4];  [12];  [23];  [24];  [13];  [25];  [1];  [11];  [10];  [20]; ORCiD logo [26];  [11]; ORCiD logo [3];  [2];  [27]; ORCiD logo [1];  [4] « less
  1. Center for Genome Research and Biocomputing, Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR 97331, USA
  2. Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA 94710, USA
  3. The Jackson Laboratory For Genomic Medicine, Farmington, CT 06032, USA
  4. European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
  5. Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, OR 97239, USA
  6. Renaissance Computing Institute at UNC, Chapel Hill, NC 27517, USA
  7. Broad Institute, Cambridge, MA 02142, USA
  8. The Jackson Laboratory, Bar Harbor, ME 04609, USA
  9. Institute of Neuroscience, University of Oregon, Eugene, OR 97401, USA
  10. College of Public Health and Human Sciences, Oregon State University, Corvallis, OR 97331, USA
  11. William Harvey Research Institute, Barts & The London School of Medicine & Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
  12. Rothamsted Research, Harpenden AL5 2JQ, UK
  13. Office of Rare Diseases Research (ORDR), National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Bethesda, MD 20892, USA
  14. dictyBase, Center for Genetic Medicine, Northwestern University, Chicago, IL 60611, USA
  15. California Institute of Technology, Pasadena, CA 91125, USA
  16. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
  17. University of Cambridge, Cambridge CB2 1TN, UK
  18. Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA, Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA, Department of Neuropediatrics, Christian-Albrechts-University of Kiel, 24105 Kiel, Germany, Department of Neurology, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA 19104, USA
  19. Department of Biochemistry and Molecular Biology, Oregon Health & Science University, Portland, OR 97239, USA
  20. Pryzm Health, 4215 Queensland, Australia
  21. Autism & Developmental Medicine Institute, Geisinger, Danville, PA 17837, USA
  22. Stowers Institute for Medical Research, Kansas City, MO 64110, USA
  23. Xenbase, Cincinnati Children's Hospital, Cincinnati, OH 45229, USA
  24. National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
  25. University of North Carolina Medical School, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
  26. Institute for Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany
  27. Center for Genome Research and Biocomputing, Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR 97331, USA, Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, OR 97239, USA
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES); National Institutes of Health (NIH); The Monarch Initiative; Forums for Integrative Phenomics; Core Funds, Open Targets; European Union’s Horizon 2020 Research and Innovation Programme; National Human Genome Research Institute (NHGRI); Medical Research Council (MRC); Biotechnology and Biological Sciences Research Council (BBSRC)
Contributing Org.:
Monarch Team
OSTI Identifier:
1573519
Alternate Identifier(s):
OSTI ID: 1615289
Grant/Contract Number:  
AC02-05CH11231; U24 HG002223; U41HG000330; U41 HG002659
Resource Type:
Published Article
Journal Name:
Nucleic Acids Research
Additional Journal Information:
Journal Name: Nucleic Acids Research Journal Volume: 48 Journal Issue: D1; Journal ID: ISSN 0305-1048
Publisher:
Oxford University Press
Country of Publication:
United Kingdom
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES

Citation Formats

Shefchek, Kent A., Harris, Nomi L., Gargano, Michael, Matentzoglu, Nicolas, Unni, Deepak, Brush, Matthew, Keith, Daniel, Conlin, Tom, Vasilevsky, Nicole, Zhang, Xingmin Aaron, Balhoff, James P., Babb, Larry, Bello, Susan M., Blau, Hannah, Bradford, Yvonne, Carbon, Seth, Carmody, Leigh, Chan, Lauren E., Cipriani, Valentina, Cuzick, Alayne, Della Rocca, Maria, Dunn, Nathan, Essaid, Shahim, Fey, Petra, Grove, Chris, Gourdine, Jean-Phillipe, Hamosh, Ada, Harris, Midori, Helbig, Ingo, Hoatlin, Maureen, Joachimiak, Marcin, Jupp, Simon, Lett, Kenneth B., Lewis, Suzanna E., McNamara, Craig, Pendlington, Zoë M., Pilgrim, Clare, Putman, Tim, Ravanmehr, Vida, Reese, Justin, Riggs, Erin, Robb, Sofia, Roncaglia, Paola, Seager, James, Segerdell, Erik, Similuk, Morgan, Storm, Andrea L., Thaxon, Courtney, Thessen, Anne, Jacobsen, Julius O. B., McMurry, Julie A., Groza, Tudor, Köhler, Sebastian, Smedley, Damian, Robinson, Peter N., Mungall, Christopher J., Haendel, Melissa A., Munoz-Torres, Monica C., and Osumi-Sutherland, David. The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species. United Kingdom: N. p., 2019. Web. doi:10.1093/nar/gkz997.
Shefchek, Kent A., Harris, Nomi L., Gargano, Michael, Matentzoglu, Nicolas, Unni, Deepak, Brush, Matthew, Keith, Daniel, Conlin, Tom, Vasilevsky, Nicole, Zhang, Xingmin Aaron, Balhoff, James P., Babb, Larry, Bello, Susan M., Blau, Hannah, Bradford, Yvonne, Carbon, Seth, Carmody, Leigh, Chan, Lauren E., Cipriani, Valentina, Cuzick, Alayne, Della Rocca, Maria, Dunn, Nathan, Essaid, Shahim, Fey, Petra, Grove, Chris, Gourdine, Jean-Phillipe, Hamosh, Ada, Harris, Midori, Helbig, Ingo, Hoatlin, Maureen, Joachimiak, Marcin, Jupp, Simon, Lett, Kenneth B., Lewis, Suzanna E., McNamara, Craig, Pendlington, Zoë M., Pilgrim, Clare, Putman, Tim, Ravanmehr, Vida, Reese, Justin, Riggs, Erin, Robb, Sofia, Roncaglia, Paola, Seager, James, Segerdell, Erik, Similuk, Morgan, Storm, Andrea L., Thaxon, Courtney, Thessen, Anne, Jacobsen, Julius O. B., McMurry, Julie A., Groza, Tudor, Köhler, Sebastian, Smedley, Damian, Robinson, Peter N., Mungall, Christopher J., Haendel, Melissa A., Munoz-Torres, Monica C., & Osumi-Sutherland, David. The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species. United Kingdom. https://doi.org/10.1093/nar/gkz997
Shefchek, Kent A., Harris, Nomi L., Gargano, Michael, Matentzoglu, Nicolas, Unni, Deepak, Brush, Matthew, Keith, Daniel, Conlin, Tom, Vasilevsky, Nicole, Zhang, Xingmin Aaron, Balhoff, James P., Babb, Larry, Bello, Susan M., Blau, Hannah, Bradford, Yvonne, Carbon, Seth, Carmody, Leigh, Chan, Lauren E., Cipriani, Valentina, Cuzick, Alayne, Della Rocca, Maria, Dunn, Nathan, Essaid, Shahim, Fey, Petra, Grove, Chris, Gourdine, Jean-Phillipe, Hamosh, Ada, Harris, Midori, Helbig, Ingo, Hoatlin, Maureen, Joachimiak, Marcin, Jupp, Simon, Lett, Kenneth B., Lewis, Suzanna E., McNamara, Craig, Pendlington, Zoë M., Pilgrim, Clare, Putman, Tim, Ravanmehr, Vida, Reese, Justin, Riggs, Erin, Robb, Sofia, Roncaglia, Paola, Seager, James, Segerdell, Erik, Similuk, Morgan, Storm, Andrea L., Thaxon, Courtney, Thessen, Anne, Jacobsen, Julius O. B., McMurry, Julie A., Groza, Tudor, Köhler, Sebastian, Smedley, Damian, Robinson, Peter N., Mungall, Christopher J., Haendel, Melissa A., Munoz-Torres, Monica C., and Osumi-Sutherland, David. Fri . "The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species". United Kingdom. https://doi.org/10.1093/nar/gkz997.
@article{osti_1573519,
title = {The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species},
author = {Shefchek, Kent A. and Harris, Nomi L. and Gargano, Michael and Matentzoglu, Nicolas and Unni, Deepak and Brush, Matthew and Keith, Daniel and Conlin, Tom and Vasilevsky, Nicole and Zhang, Xingmin Aaron and Balhoff, James P. and Babb, Larry and Bello, Susan M. and Blau, Hannah and Bradford, Yvonne and Carbon, Seth and Carmody, Leigh and Chan, Lauren E. and Cipriani, Valentina and Cuzick, Alayne and Della Rocca, Maria and Dunn, Nathan and Essaid, Shahim and Fey, Petra and Grove, Chris and Gourdine, Jean-Phillipe and Hamosh, Ada and Harris, Midori and Helbig, Ingo and Hoatlin, Maureen and Joachimiak, Marcin and Jupp, Simon and Lett, Kenneth B. and Lewis, Suzanna E. and McNamara, Craig and Pendlington, Zoë M. and Pilgrim, Clare and Putman, Tim and Ravanmehr, Vida and Reese, Justin and Riggs, Erin and Robb, Sofia and Roncaglia, Paola and Seager, James and Segerdell, Erik and Similuk, Morgan and Storm, Andrea L. and Thaxon, Courtney and Thessen, Anne and Jacobsen, Julius O. B. and McMurry, Julie A. and Groza, Tudor and Köhler, Sebastian and Smedley, Damian and Robinson, Peter N. and Mungall, Christopher J. and Haendel, Melissa A. and Munoz-Torres, Monica C. and Osumi-Sutherland, David},
abstractNote = {In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.},
doi = {10.1093/nar/gkz997},
journal = {Nucleic Acids Research},
number = D1,
volume = 48,
place = {United Kingdom},
year = {Fri Nov 08 00:00:00 EST 2019},
month = {Fri Nov 08 00:00:00 EST 2019}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1093/nar/gkz997

Citation Metrics:
Cited by: 102 works
Citation information provided by
Web of Science

Figures / Tables:

Figure 1 Figure 1: uPheno template-driven ontology development and harmonization. uPheno templates are used to define phenotypes according to agreed upon design patterns. (A). Computable definitions specified using uPheno templates are used to automate classification of uPheno and parts of the Zebrafish Phenotype Ontology (ZP (13); dashed lines). (B). Computable definitions alsomore » drive automated classification of HPO and ZP classes under uPheno classes. For example, enlarged heart in ZP (defined using the zebrafish anatomy heart term) and enlarged heart in HPO are both classified under uPheno enlarged heart (defined using Uberon heart). Algorithms can use this classification under uPheno to predict that human orthologs of zebrafish genes annotated to enlarged heart may cause enlarged heart in humans.« less

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