Reconstruction of Mitochondrial Genotypes from Diverse next Generation Sequencing Datasets
Peter Ulz, Michael R. Speicher, Gerhard G. Thallinger
2017
Abstract
The exponential growth of sequence databases in recent years opens up a lot of possibilities for reanalysis of public datasets. Here, we reanalyzed sequencing data from various experimental procedures to reconstruct the mitochondrial genome from sequence data of human samples. In a first step eight human cell lines were used to validate the approach and to ensure consistent genotype information across different library preparation techniques. Subsequently, 19,337 sequencing datasets were downloaded and checked for single-nucleotide variants and insertion or deletion events. We show that the mitochondrial genome can be inferred from many different library preparation techniques. We also generated reference mitochondrial genomes for eight cell lines. This approach may be used for sample identification as well as a general approach to study the mitochondrial genome from public sequencing data.
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in Harvard Style
Ulz P., Speicher M. and Thallinger G. (2017). Reconstruction of Mitochondrial Genotypes from Diverse next Generation Sequencing Datasets. In - BIOINFORMATICS, (BIOSTEC 2017) ISBN , pages 0-0. DOI: 10.5220/0006110200001488
in Bibtex Style
@conference{bioinformatics17,
author={Peter Ulz and Michael R. Speicher and Gerhard G. Thallinger},
title={Reconstruction of Mitochondrial Genotypes from Diverse next Generation Sequencing Datasets},
booktitle={ - BIOINFORMATICS, (BIOSTEC 2017)},
year={2017},
pages={},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006110200001488},
isbn={},
}
in EndNote Style
TY - CONF
JO - - BIOINFORMATICS, (BIOSTEC 2017)
TI - Reconstruction of Mitochondrial Genotypes from Diverse next Generation Sequencing Datasets
SN -
AU - Ulz P.
AU - Speicher M.
AU - Thallinger G.
PY - 2017
SP - 0
EP - 0
DO - 10.5220/0006110200001488