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VCF.Filter: interactive prioritization of disease-linked genetic variants from sequencing data

Next generation sequencing is widely used to link genetic variants to diseases, and it has massively accelerated the diagnosis and characterization of rare genetic diseases. After initial bioinformatic data processing, the interactive analysis of genome, exome, and panel sequencing data typically st...

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Autores principales: Müller, Heiko, Jimenez-Heredia, Raul, Krolo, Ana, Hirschmugl, Tatjana, Dmytrus, Jasmin, Boztug, Kaan, Bock, Christoph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5570181/
https://www.ncbi.nlm.nih.gov/pubmed/28520890
http://dx.doi.org/10.1093/nar/gkx425
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author Müller, Heiko
Jimenez-Heredia, Raul
Krolo, Ana
Hirschmugl, Tatjana
Dmytrus, Jasmin
Boztug, Kaan
Bock, Christoph
author_facet Müller, Heiko
Jimenez-Heredia, Raul
Krolo, Ana
Hirschmugl, Tatjana
Dmytrus, Jasmin
Boztug, Kaan
Bock, Christoph
author_sort Müller, Heiko
collection PubMed
description Next generation sequencing is widely used to link genetic variants to diseases, and it has massively accelerated the diagnosis and characterization of rare genetic diseases. After initial bioinformatic data processing, the interactive analysis of genome, exome, and panel sequencing data typically starts from lists of genetic variants in VCF format. Medical geneticists filter and annotate these lists to identify variants that may be relevant for the disease under investigation, or to select variants that are reported in a clinical diagnostics setting. We developed VCF.Filter to facilitate the search for disease-linked variants, providing a standalone Java program with a user-friendly interface for interactive variant filtering and annotation. VCF.Filter allows the user to define a broad range of filtering criteria through a graphical interface. Common workflows such as trio analysis and cohort-based filtering are pre-configured, and more complex analyses can be performed using VCF.Filter's support for custom annotations and filtering criteria. All filtering is documented in the results file, thus providing traceability of the interactive variant prioritization. VCF.Filter is an open source tool that is freely and openly available at http://vcffilter.rarediseases.at.
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spelling pubmed-55701812017-08-29 VCF.Filter: interactive prioritization of disease-linked genetic variants from sequencing data Müller, Heiko Jimenez-Heredia, Raul Krolo, Ana Hirschmugl, Tatjana Dmytrus, Jasmin Boztug, Kaan Bock, Christoph Nucleic Acids Res Web Server Issue Next generation sequencing is widely used to link genetic variants to diseases, and it has massively accelerated the diagnosis and characterization of rare genetic diseases. After initial bioinformatic data processing, the interactive analysis of genome, exome, and panel sequencing data typically starts from lists of genetic variants in VCF format. Medical geneticists filter and annotate these lists to identify variants that may be relevant for the disease under investigation, or to select variants that are reported in a clinical diagnostics setting. We developed VCF.Filter to facilitate the search for disease-linked variants, providing a standalone Java program with a user-friendly interface for interactive variant filtering and annotation. VCF.Filter allows the user to define a broad range of filtering criteria through a graphical interface. Common workflows such as trio analysis and cohort-based filtering are pre-configured, and more complex analyses can be performed using VCF.Filter's support for custom annotations and filtering criteria. All filtering is documented in the results file, thus providing traceability of the interactive variant prioritization. VCF.Filter is an open source tool that is freely and openly available at http://vcffilter.rarediseases.at. Oxford University Press 2017-07-03 2017-05-17 /pmc/articles/PMC5570181/ /pubmed/28520890 http://dx.doi.org/10.1093/nar/gkx425 Text en © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Web Server Issue
Müller, Heiko
Jimenez-Heredia, Raul
Krolo, Ana
Hirschmugl, Tatjana
Dmytrus, Jasmin
Boztug, Kaan
Bock, Christoph
VCF.Filter: interactive prioritization of disease-linked genetic variants from sequencing data
title VCF.Filter: interactive prioritization of disease-linked genetic variants from sequencing data
title_full VCF.Filter: interactive prioritization of disease-linked genetic variants from sequencing data
title_fullStr VCF.Filter: interactive prioritization of disease-linked genetic variants from sequencing data
title_full_unstemmed VCF.Filter: interactive prioritization of disease-linked genetic variants from sequencing data
title_short VCF.Filter: interactive prioritization of disease-linked genetic variants from sequencing data
title_sort vcf.filter: interactive prioritization of disease-linked genetic variants from sequencing data
topic Web Server Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5570181/
https://www.ncbi.nlm.nih.gov/pubmed/28520890
http://dx.doi.org/10.1093/nar/gkx425
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