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

A - Papers appearing in refereed journals

Shefchek, K. A., Harris, N. L., Gargano, M., Matentzoglu, N., Unni, D., Brush, M., Keith, D., Conlin, T., Vasilevsky, N., Zhang, X. A., Balhoff, J. P., Babb, L., Bello, S. M., Blau, H., Bradford, Y., Carbon, S., Carmody, L., Chan, L. E., Cipriani, V., Cuzick, A., Rocca, M. D., Dunn, N., Essaid, S., Fey, P., Grove, C., Gourdine, J., Hamosh, A., Harris, M., Helbig, I., Hoatlin, M., Joachimiak, M., Jupp, S., Lett, K. B., Lewis, S. E., McNamara, C., Pendlington, Z. M., Pilgrim, C., Putman, T., Ravanmehr, V., Reese, J., Riggs, E., Robb, S., Roncaglia, P., Seager, J., Segerdell, E., Similuk, M., Storm, A. L., Thaxon, C., Thessen, A., Jacobsen, J. O. B., McMurry, J. A., Groza, T., Köhler, S., Smedley, D., Robinson, P. N., Mungall, C. J., Haendel, M. A., Munoz-Torres, M. C. and Osumi-Sutherland, D. 2020. The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species. Nucleic Acids Research. 48 (D1), p. D704–D715. https://doi.org/10.1093/nar/gkz997

AuthorsShefchek, K. A., Harris, N. L., Gargano, M., Matentzoglu, N., Unni, D., Brush, M., Keith, D., Conlin, T., Vasilevsky, N., Zhang, X. A., Balhoff, J. P., Babb, L., Bello, S. M., Blau, H., Bradford, Y., Carbon, S., Carmody, L., Chan, L. E., Cipriani, V., Cuzick, A., Rocca, M. D., Dunn, N., Essaid, S., Fey, P., Grove, C., Gourdine, J., Hamosh, A., Harris, M., Helbig, I., Hoatlin, M., Joachimiak, M., Jupp, S., Lett, K. B., Lewis, S. E., McNamara, C., Pendlington, Z. M., Pilgrim, C., Putman, T., Ravanmehr, V., Reese, J., Riggs, E., Robb, S., Roncaglia, P., Seager, J., Segerdell, E., Similuk, M., Storm, A. L., Thaxon, C., Thessen, A., Jacobsen, J. O. B., McMurry, J. A., Groza, T., Köhler, S., Smedley, D., Robinson, P. N., Mungall, C. J., Haendel, M. A., Munoz-Torres, M. C. and Osumi-Sutherland, D.
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.

Year of Publication2020
JournalNucleic Acids Research
Journal citation48 (D1), p. D704–D715
Digital Object Identifier (DOI)https://doi.org/10.1093/nar/gkz997
PubMed ID31701156
PubMed Central IDPMC7056945
Open accessPublished as ‘gold’ (paid) open access
FunderBiotechnology and Biological Sciences Research Council
Publisher's version
Copyright license
Open Government Licence
Output statusPublished
Publication dates
Online08 Nov 2019
Publication process dates
Accepted14 Oct 2019
PublisherOxford University Press (OUP)
Other fileThe%20Monarch%20Initiative%20in%202019%3A%20an%20integrative%20data%20and%20analytic%20platform%20connecting%20phenotypes%20to%20genotypes%20across%20species.%20.pdf
ISSN0305-1048

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