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  • Original Article
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Quality control metrics improve repeatability and reproducibility of single-nucleotide variants derived from whole-genome sequencing

The Pharmacogenomics Journal volume 15, pages 298–309 (2015)Cite this article

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Abstract

Although many quality control (QC) methods have been developed to improve the quality of single-nucleotide variants (SNVs) in SNV-calling, QC methods for use subsequent to single-nucleotide polymorphism-calling have not been reported. We developed five QC metrics to improve the quality of SNVs using the whole-genome-sequencing data of a monozygotic twin pair from the Korean Personal Genome Project. The QC metrics improved both repeatability between the monozygotic twin pair and reproducibility between SNV-calling pipelines. We demonstrated the QC metrics improve reproducibility of SNVs derived from not only whole-genome-sequencing data but also whole-exome-sequencing data. The QC metrics are calculated based on the reference genome used in the alignment without accessing the raw and intermediate data or knowing the SNV-calling details. Therefore, the QC metrics can be easily adopted in downstream association analysis.

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Acknowledgements

This research was supported in part by an appointment to the Research Participation Program at the National Center for Toxicological Research (WZ and HWN) and at the Center for Biologics Evaluation and Research (VS) administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the US Department of Energy and the US Food and Drug Administration (FDA). We thank Mike Mikailov of FDA’s Center for Devices and Radiological Health for his technical support on the data analysis conducted on the high-performance computation cluster Betsy in the White Oak Data Center of FDA. We acknowledge Critical Assessment of Massive Data Analysis consortium for providing us the raw data, as well as the mapping and SNVs calling results from KPGP. The findings and conclusions in this article have not been formally disseminated by the US FDA and should not be construed to represent any agency determination or policy.

Author Contributions

HH, WZ, WT and RP conceived the study and designed the experiments. WZ, VS (Valerii Soika), JM, ZS, WG, HWN and HH performed the data analysis. HH, WZ, RP and WT wrote the paper with assistance from the other authors. All authors have read and approved the manuscript for publication.

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Authors and Affiliations

  1. Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA

    W Zhang, J Meehan, Z Su, W Ge, H W Ng, R Perkins, W Tong & H Hong

  2. Office of The Center Director, Center for Biologics Evaluation and Research, US Food and Drug Administration, Rockville, MD, USA

    V Soika & V Simonyan

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  1. W Zhang
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Correspondence to H Hong.

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Zhang, W., Soika, V., Meehan, J. et al. Quality control metrics improve repeatability and reproducibility of single-nucleotide variants derived from whole-genome sequencing. Pharmacogenomics J 15, 298–309 (2015). https://doi.org/10.1038/tpj.2014.70

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