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Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study

Zhao, Y., Fang, L.T., Shen, T-W, Choudhari, S., Talsania, K., Chen, X., Shetty, J., Kriga, Y., Tran, B., Zhu, B., Chen, Z., Chen, W., Wang, C., Jaeger, E., Meerzaman, D., Lu, C., Idler, K., Ren, L., Zheng, Y., Shi, L., Petitjean, V., Sultan, M., Hung, T., Peters, E., Drabek, J., Vojta, P., Maestro, R., Gasparotto, D., Kõks, S., Reimann, E., Scherer, A., Nordlund, J., Liljedahl, U., Foox, J., Mason, C.E., Xiao, C., Hong, H. and Xiao, W. (2021) Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study. Scientific Data, 8 (1). Art. 296.

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Free to read: https://doi.org/10.1038/s41597-021-01077-5
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Abstract

With the rapid advancement of sequencing technologies, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples and generated whole-genome (WGS) and whole-exome sequencing (WES) data using sixteen library protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies.

Item Type: Journal Article
Murdoch Affiliation(s): Centre for Molecular Medicine and Innovative Therapeutics (CMMIT)
Publisher: Springer Nature
Copyright: © 2021 Yongmei Zhao et al.
URI: http://researchrepository.murdoch.edu.au/id/eprint/62987
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