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Nucleic Acids Res. 2016 Jul 8;44(W1):W64-9. doi: 10.1093/nar/gkw247. Epub 2016 Apr 15.

mtDNA-Server: next-generation sequencing data analysis of human mitochondrial DNA in the cloud.

Author information

1
Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck 6020, Austria Department of Database and Information Systems, Institute of Computer Science, University of Innsbruck, Innsbruck 6020, Austria.
2
Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck 6020, Austria.
3
Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck 6020, Austria Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor 48109, Michigan, USA.
4
Department of Database and Information Systems, Institute of Computer Science, University of Innsbruck, Innsbruck 6020, Austria.
5
Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck 6020, Austria sebastian.schoenherr@i-med.ac.at.

Abstract

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.

PMID:
27084948
PMCID:
PMC4987870
DOI:
10.1093/nar/gkw247
[Indexed for MEDLINE]
Free PMC Article

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