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Genomic variant annotation workflow for clinical applications

Annotation and interpretation of DNA aberrations identified through next-generation sequencing is becoming an increasingly important task. Even more so in the context of data analysis pipelines for medical applications, where genomic aberrations are associated with phenotypic and clinical features....

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Detalles Bibliográficos
Autores principales: Thurnherr, Thomas, Singer, Franziska, Stekhoven, Daniel J., Beerenwinkel, Niko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000Research 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5130070/
https://www.ncbi.nlm.nih.gov/pubmed/27990260
http://dx.doi.org/10.12688/f1000research.9357.2
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author Thurnherr, Thomas
Singer, Franziska
Stekhoven, Daniel J.
Beerenwinkel, Niko
author_facet Thurnherr, Thomas
Singer, Franziska
Stekhoven, Daniel J.
Beerenwinkel, Niko
author_sort Thurnherr, Thomas
collection PubMed
description Annotation and interpretation of DNA aberrations identified through next-generation sequencing is becoming an increasingly important task. Even more so in the context of data analysis pipelines for medical applications, where genomic aberrations are associated with phenotypic and clinical features. Here we describe a workflow to identify potential gene targets in aberrated genes or pathways and their corresponding drugs. To this end, we provide the R/Bioconductor package rDGIdb, an R wrapper to query the drug-gene interaction database (DGIdb). DGIdb accumulates drug-gene interaction data from 15 different resources and allows filtering on different levels. The rDGIdb package makes these resources and tools available to R users. Moreover, rDGIdb queries can be automated through incorporation of the rDGIdb package into NGS sequencing pipelines.
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spelling pubmed-51300702016-12-16 Genomic variant annotation workflow for clinical applications Thurnherr, Thomas Singer, Franziska Stekhoven, Daniel J. Beerenwinkel, Niko F1000Res Software Tool Article Annotation and interpretation of DNA aberrations identified through next-generation sequencing is becoming an increasingly important task. Even more so in the context of data analysis pipelines for medical applications, where genomic aberrations are associated with phenotypic and clinical features. Here we describe a workflow to identify potential gene targets in aberrated genes or pathways and their corresponding drugs. To this end, we provide the R/Bioconductor package rDGIdb, an R wrapper to query the drug-gene interaction database (DGIdb). DGIdb accumulates drug-gene interaction data from 15 different resources and allows filtering on different levels. The rDGIdb package makes these resources and tools available to R users. Moreover, rDGIdb queries can be automated through incorporation of the rDGIdb package into NGS sequencing pipelines. F1000Research 2016-10-24 /pmc/articles/PMC5130070/ /pubmed/27990260 http://dx.doi.org/10.12688/f1000research.9357.2 Text en Copyright: © 2016 Thurnherr T et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software Tool Article
Thurnherr, Thomas
Singer, Franziska
Stekhoven, Daniel J.
Beerenwinkel, Niko
Genomic variant annotation workflow for clinical applications
title Genomic variant annotation workflow for clinical applications
title_full Genomic variant annotation workflow for clinical applications
title_fullStr Genomic variant annotation workflow for clinical applications
title_full_unstemmed Genomic variant annotation workflow for clinical applications
title_short Genomic variant annotation workflow for clinical applications
title_sort genomic variant annotation workflow for clinical applications
topic Software Tool Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5130070/
https://www.ncbi.nlm.nih.gov/pubmed/27990260
http://dx.doi.org/10.12688/f1000research.9357.2
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