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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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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. |
format | Online Article Text |
id | pubmed-5570181 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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