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mtDNA-Server: next-generation sequencing data analysis of human mitochondrial DNA in the cloud
Next generation sequencing (NGS) allows investigating mitochondrial DNA (mtDNA) characteristics such as heteroplasmy (i.e. intra-individual sequence variation) to a higher level of detail. While several pipelines for analyzing heteroplasmies exist, issues in usability, accuracy of results and interp...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4987870/ https://www.ncbi.nlm.nih.gov/pubmed/27084948 http://dx.doi.org/10.1093/nar/gkw247 |
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author | Weissensteiner, Hansi Forer, Lukas Fuchsberger, Christian Schöpf, Bernd Kloss-Brandstätter, Anita Specht, Günther Kronenberg, Florian Schönherr, Sebastian |
author_facet | Weissensteiner, Hansi Forer, Lukas Fuchsberger, Christian Schöpf, Bernd Kloss-Brandstätter, Anita Specht, Günther Kronenberg, Florian Schönherr, Sebastian |
author_sort | Weissensteiner, Hansi |
collection | PubMed |
description | Next generation sequencing (NGS) allows investigating mitochondrial DNA (mtDNA) characteristics such as heteroplasmy (i.e. intra-individual sequence variation) to a higher level of detail. While several pipelines for analyzing heteroplasmies exist, issues in usability, accuracy of results and interpreting final data limit their usage. Here we present mtDNA-Server, a scalable web server for the analysis of mtDNA studies of any size with a special focus on usability as well as reliable identification and quantification of heteroplasmic variants. The mtDNA-Server workflow includes parallel read alignment, heteroplasmy detection, artefact or contamination identification, variant annotation as well as several quality control metrics, often neglected in current mtDNA NGS studies. All computational steps are parallelized with Hadoop MapReduce and executed graphically with Cloudgene. We validated the underlying heteroplasmy and contamination detection model by generating four artificial sample mix-ups on two different NGS devices. Our evaluation data shows that mtDNA-Server detects heteroplasmies and artificial recombinations down to the 1% level with perfect specificity and outperforms existing approaches regarding sensitivity. mtDNA-Server is currently able to analyze the 1000G Phase 3 data (n = 2,504) in less than 5 h and is freely accessible at https://mtdna-server.uibk.ac.at. |
format | Online Article Text |
id | pubmed-4987870 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-49878702016-08-22 mtDNA-Server: next-generation sequencing data analysis of human mitochondrial DNA in the cloud Weissensteiner, Hansi Forer, Lukas Fuchsberger, Christian Schöpf, Bernd Kloss-Brandstätter, Anita Specht, Günther Kronenberg, Florian Schönherr, Sebastian Nucleic Acids Res Web Server issue Next generation sequencing (NGS) allows investigating mitochondrial DNA (mtDNA) characteristics such as heteroplasmy (i.e. intra-individual sequence variation) to a higher level of detail. While several pipelines for analyzing heteroplasmies exist, issues in usability, accuracy of results and interpreting final data limit their usage. Here we present mtDNA-Server, a scalable web server for the analysis of mtDNA studies of any size with a special focus on usability as well as reliable identification and quantification of heteroplasmic variants. The mtDNA-Server workflow includes parallel read alignment, heteroplasmy detection, artefact or contamination identification, variant annotation as well as several quality control metrics, often neglected in current mtDNA NGS studies. All computational steps are parallelized with Hadoop MapReduce and executed graphically with Cloudgene. We validated the underlying heteroplasmy and contamination detection model by generating four artificial sample mix-ups on two different NGS devices. Our evaluation data shows that mtDNA-Server detects heteroplasmies and artificial recombinations down to the 1% level with perfect specificity and outperforms existing approaches regarding sensitivity. mtDNA-Server is currently able to analyze the 1000G Phase 3 data (n = 2,504) in less than 5 h and is freely accessible at https://mtdna-server.uibk.ac.at. Oxford University Press 2016-07-08 2016-04-15 /pmc/articles/PMC4987870/ /pubmed/27084948 http://dx.doi.org/10.1093/nar/gkw247 Text en © The Author(s) 2016. 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 Weissensteiner, Hansi Forer, Lukas Fuchsberger, Christian Schöpf, Bernd Kloss-Brandstätter, Anita Specht, Günther Kronenberg, Florian Schönherr, Sebastian mtDNA-Server: next-generation sequencing data analysis of human mitochondrial DNA in the cloud |
title | mtDNA-Server: next-generation sequencing data analysis of human mitochondrial DNA in the cloud |
title_full | mtDNA-Server: next-generation sequencing data analysis of human mitochondrial DNA in the cloud |
title_fullStr | mtDNA-Server: next-generation sequencing data analysis of human mitochondrial DNA in the cloud |
title_full_unstemmed | mtDNA-Server: next-generation sequencing data analysis of human mitochondrial DNA in the cloud |
title_short | mtDNA-Server: next-generation sequencing data analysis of human mitochondrial DNA in the cloud |
title_sort | mtdna-server: next-generation sequencing data analysis of human mitochondrial dna in the cloud |
topic | Web Server issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4987870/ https://www.ncbi.nlm.nih.gov/pubmed/27084948 http://dx.doi.org/10.1093/nar/gkw247 |
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