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

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 prioritizatio...

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Autores principales:	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
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/8256eeb26c5746a9a9e8d6dcd1fd68ae
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spelling	oai:doaj.org-article:8256eeb26c5746a9a9e8d6dcd1fd68ae2021-12-02T16:57:54ZImproving the diagnostic yield of exome- sequencing by predicting gene–phenotype associations using large-scale gene expression analysis10.1038/s41467-019-10649-42041-1723https://doaj.org/article/8256eeb26c5746a9a9e8d6dcd1fd68ae2019-06-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-10649-4https://doaj.org/toc/2041-1723A 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.Patrick DeelenSipko van DamJohanna C. HerkertJuha M. KarjalainenHarm BruggeKristin M. AbbottCleo C. van DiemenPaul A. van der ZwaagErica H. GerkesEvelien Zonneveld-HuijssoonJelkje J. Boer-BergsmaPytrik FolkertsmaTessa GillettK. Joeri van der VeldeRoan KanningaPeter C. van den AkkerSabrina Z. JanEdgar T. HoorntjeWouter P. te RijdtYvonne J. VosJan D. H. JongbloedConny M. A. van Ravenswaaij-ArtsRichard SinkeBirgit Sikkema-RaddatzWilhelmina S. Kerstjens-FrederikseMorris A. SwertzLude FrankeNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-13 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q 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 Improving the diagnostic yield of exome- sequencing by predicting gene–phenotype associations using large-scale gene expression analysis
description	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.
format	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
author_facet	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
author_sort	Patrick Deelen
title	Improving the diagnostic yield of exome- sequencing by predicting gene–phenotype associations using large-scale gene expression analysis
title_short	Improving the diagnostic yield of exome- sequencing by predicting gene–phenotype associations using large-scale gene expression analysis
title_full	Improving the diagnostic yield of exome- sequencing by predicting gene–phenotype associations using large-scale gene expression analysis
title_fullStr	Improving the diagnostic yield of exome- sequencing by predicting gene–phenotype associations using large-scale gene expression analysis
title_full_unstemmed	Improving the diagnostic yield of exome- sequencing by predicting gene–phenotype associations using large-scale gene expression analysis
title_sort	improving the diagnostic yield of exome- sequencing by predicting gene–phenotype associations using large-scale gene expression analysis
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/8256eeb26c5746a9a9e8d6dcd1fd68ae
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Improving the diagnostic yield of exome- sequencing by predicting gene–phenotype associations using large-scale gene expression analysis

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