Improving the diagnostic yield of exome- sequencing by predicting gene–phenotype associations using large-scale gene expression analysis

The diagnostic yield of exome and genome sequencing remains low (8–70%), due to incomplete knowledge on the genes that cause disease. To improve this, we use RNA-seq data from 31,499 samples to predict which genes cause specific disease phenotypes, and develop GeneNetwork Assisted Diagnostic Optimiz...

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Detalles Bibliográficos
Autores principales: Deelen, Patrick, van Dam, Sipko, Herkert, Johanna C., Karjalainen, Juha M., Brugge, Harm, Abbott, Kristin M., van Diemen, Cleo C., van der Zwaag, Paul A., Gerkes, Erica H., Zonneveld-Huijssoon, Evelien, Boer-Bergsma, Jelkje J., Folkertsma, Pytrik, Gillett, Tessa, van der Velde, K. Joeri, Kanninga, Roan, van den Akker, Peter C., Jan, Sabrina Z., Hoorntje, Edgar T., te Rijdt, Wouter P., Vos, Yvonne J., Jongbloed, Jan D. H., van Ravenswaaij-Arts, Conny M. A., Sinke, Richard, Sikkema-Raddatz, Birgit, Kerstjens-Frederikse, Wilhelmina S., Swertz, Morris A., Franke, Lude
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6599066/
https://www.ncbi.nlm.nih.gov/pubmed/31253775
http://dx.doi.org/10.1038/s41467-019-10649-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6599066/
https://www.ncbi.nlm.nih.gov/pubmed/31253775
http://dx.doi.org/10.1038/s41467-019-10649-4

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