Predicting genes from phenotypes using human phenotype ontology (HPO) terms
Author:
Funder
National Human Genome Research Institute
Publisher
Springer Science and Business Media LLC
Subject
Genetics (clinical),Genetics
Link
https://link.springer.com/content/pdf/10.1007/s00439-022-02449-6.pdf
Reference35 articles.
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3. Clark MM, Stark Z, Farnaes L, Tan TY, White SM, Dimmock D, Kingsmore SF (2018) Meta-analysis of the diagnostic and clinical utility of genome and whole exome sequencingand chromosomal microarray in children with suspected genetic diseases. NPJ Genom Med 3:16. https://doi.org/10.1038/s41525-018-0053-8
4. Deelen P, van Dam S, Herkert JC, Karjalainen JM, Brugge H, Abbott KM, van Diemen CC, van der Zwaag PA, Gerkes EH, Zonneveld-Huijssoon E, Boer-Bergsma JJ, Folkertsma P, Gillett T, van der Velde KJ, Kanninga R, van den Akker PC, Jan SZ, Hoorntje ET, Te Rijdt WP, Vos YJ, Jongbloed JDH, van Ravenswaaij-Arts CMA, Sinke R, Sikkema-Raddatz B, Kerstjens-Frederikse WS, Swertz MA, Franke L (2019) Improving the diagnostic yield of exome- sequencing by predicting gene-phenotype associations using large-scale gene expression analysis. Nat Commun 10(1):2837. https://doi.org/10.1038/s41467-019-10649-4
5. Deisseroth CA, Birgmeier J, Bodle EE, Kohler JN, Matalon DR, Nazarenko Y, Genetti CA, Brownstein CA, Schmitz-Abe K, Schoch K, Cope H, Signer R, Network UD, Martinez-Agosto JA, Shashi V, Beggs AH, Wheeler MT, Bernstein JA, Bejerano G (2019) ClinPhen extracts and prioritizes patient phenotypes directly from medical records to expedite genetic disease diagnosis. Genet Med 21(7):1585–1593
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