학술논문
Improving the diagnostic yield of exome- sequencing by predicting gene–phenotype associations using large-scale gene expression analysis
Document Type
article
Author
Patrick Deelen; Sipko van Dam; Johanna C. Herkert; Juha M. Karjalainen; Harm Brugge; Kristin M. Abbott; Cleo C. van Diemen; Paul A. van der Zwaag; Erica H. Gerkes; Evelien Zonneveld-Huijssoon; Jelkje J. Boer-Bergsma; Pytrik Folkertsma; Tessa Gillett; K. Joeri van der Velde; Roan Kanninga; Peter C. van den Akker; Sabrina Z. Jan; Edgar T. Hoorntje; Wouter P. te Rijdt; Yvonne J. Vos; Jan D. H. Jongbloed; Conny M. A. van Ravenswaaij-Arts; Richard Sinke; Birgit Sikkema-Raddatz; Wilhelmina S. Kerstjens-Frederikse; Morris A. Swertz; Lude Franke
Source
Nature Communications, Vol 10, Iss 1, Pp 1-13 (2019)
Subject
Language
English
ISSN
2041-1723
Abstract
A genetic diagnosis remains unattainable for many individuals with a rare disease because of incomplete knowledge about the genetic basis of many diseases. Here, the authors present the web-based tool GADO (GeneNetwork Assisted Diagnostic Optimization) that uses public RNA-seq data for prioritization of candidate genes.