Cargando…
VARIFI—Web-Based Automatic Variant Identification, Filtering and Annotation of Amplicon Sequencing Data
Fast and affordable benchtop sequencers are becoming more important in improving personalized medical treatment. Still, distinguishing genetic variants between healthy and diseased individuals from sequencing errors remains a challenge. Here we present VARIFI, a pipeline for finding reliable genetic...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6463100/ https://www.ncbi.nlm.nih.gov/pubmed/30717290 http://dx.doi.org/10.3390/jpm9010010 |
_version_ | 1783410701377732608 |
---|---|
author | Krunic, Milica Venhuizen, Peter Müllauer, Leonhard Kaserer, Bettina von Haeseler, Arndt |
author_facet | Krunic, Milica Venhuizen, Peter Müllauer, Leonhard Kaserer, Bettina von Haeseler, Arndt |
author_sort | Krunic, Milica |
collection | PubMed |
description | Fast and affordable benchtop sequencers are becoming more important in improving personalized medical treatment. Still, distinguishing genetic variants between healthy and diseased individuals from sequencing errors remains a challenge. Here we present VARIFI, a pipeline for finding reliable genetic variants (single nucleotide polymorphisms (SNPs) and insertions and deletions (indels)). We optimized parameters in VARIFI by analyzing more than 170 amplicon-sequenced cancer samples produced on the Personal Genome Machine (PGM). In contrast to existing pipelines, VARIFI combines different analysis methods and, based on their concordance, assigns a confidence score to each identified variant. Furthermore, VARIFI applies variant filters for biases associated with the sequencing technologies (e.g., incorrectly identified homopolymer-associated indels with Ion Torrent). VARIFI automatically extracts variant information from publicly available databases and incorporates methods for variant effect prediction. VARIFI requires little computational experience and no in-house compute power since the analyses are conducted on our server. VARIFI is a web-based tool available at varifi.cibiv.univie.ac.at. |
format | Online Article Text |
id | pubmed-6463100 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64631002019-04-19 VARIFI—Web-Based Automatic Variant Identification, Filtering and Annotation of Amplicon Sequencing Data Krunic, Milica Venhuizen, Peter Müllauer, Leonhard Kaserer, Bettina von Haeseler, Arndt J Pers Med Article Fast and affordable benchtop sequencers are becoming more important in improving personalized medical treatment. Still, distinguishing genetic variants between healthy and diseased individuals from sequencing errors remains a challenge. Here we present VARIFI, a pipeline for finding reliable genetic variants (single nucleotide polymorphisms (SNPs) and insertions and deletions (indels)). We optimized parameters in VARIFI by analyzing more than 170 amplicon-sequenced cancer samples produced on the Personal Genome Machine (PGM). In contrast to existing pipelines, VARIFI combines different analysis methods and, based on their concordance, assigns a confidence score to each identified variant. Furthermore, VARIFI applies variant filters for biases associated with the sequencing technologies (e.g., incorrectly identified homopolymer-associated indels with Ion Torrent). VARIFI automatically extracts variant information from publicly available databases and incorporates methods for variant effect prediction. VARIFI requires little computational experience and no in-house compute power since the analyses are conducted on our server. VARIFI is a web-based tool available at varifi.cibiv.univie.ac.at. MDPI 2019-02-01 /pmc/articles/PMC6463100/ /pubmed/30717290 http://dx.doi.org/10.3390/jpm9010010 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Krunic, Milica Venhuizen, Peter Müllauer, Leonhard Kaserer, Bettina von Haeseler, Arndt VARIFI—Web-Based Automatic Variant Identification, Filtering and Annotation of Amplicon Sequencing Data |
title | VARIFI—Web-Based Automatic Variant Identification, Filtering and Annotation of Amplicon Sequencing Data |
title_full | VARIFI—Web-Based Automatic Variant Identification, Filtering and Annotation of Amplicon Sequencing Data |
title_fullStr | VARIFI—Web-Based Automatic Variant Identification, Filtering and Annotation of Amplicon Sequencing Data |
title_full_unstemmed | VARIFI—Web-Based Automatic Variant Identification, Filtering and Annotation of Amplicon Sequencing Data |
title_short | VARIFI—Web-Based Automatic Variant Identification, Filtering and Annotation of Amplicon Sequencing Data |
title_sort | varifi—web-based automatic variant identification, filtering and annotation of amplicon sequencing data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6463100/ https://www.ncbi.nlm.nih.gov/pubmed/30717290 http://dx.doi.org/10.3390/jpm9010010 |
work_keys_str_mv | AT krunicmilica varifiwebbasedautomaticvariantidentificationfilteringandannotationofampliconsequencingdata AT venhuizenpeter varifiwebbasedautomaticvariantidentificationfilteringandannotationofampliconsequencingdata AT mullauerleonhard varifiwebbasedautomaticvariantidentificationfilteringandannotationofampliconsequencingdata AT kasererbettina varifiwebbasedautomaticvariantidentificationfilteringandannotationofampliconsequencingdata AT vonhaeselerarndt varifiwebbasedautomaticvariantidentificationfilteringandannotationofampliconsequencingdata |