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Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing
LT. Fang, B. Zhu, Y. Zhao, W. Chen, Z. Yang, L. Kerrigan, K. Langenbach, M. de Mars, C. Lu, K. Idler, H. Jacob, Y. Zheng, L. Ren, Y. Yu, E. Jaeger, GP. Schroth, OD. Abaan, K. Talsania, J. Lack, TW. Shen, Z. Chen, S. Stanbouly, B. Tran, J. Shetty,...
Language English Country United States
Document type Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't
Grant support
18IPA34170301
American Heart Association (American Heart Association, Inc.)
HHSN261201400008C
NCI NIH HHS - United States
HHSN261201500003I
NCI NIH HHS - United States
S10 OD019960
NIH HHS - United States
NLK
ProQuest Central
from 2000-01-01 to 1 year ago
Health & Medicine (ProQuest)
from 2000-01-01 to 1 year ago
- MeSH
- Benchmarking * MeSH
- Datasets as Topic MeSH
- Humans MeSH
- Mutation MeSH
- DNA Mutational Analysis standards MeSH
- Cell Line, Tumor MeSH
- Breast Neoplasms genetics MeSH
- Reference Standards MeSH
- Reproducibility of Results MeSH
- Whole Genome Sequencing standards MeSH
- High-Throughput Nucleotide Sequencing standards MeSH
- Germ Cells MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
The lack of samples for generating standardized DNA datasets for setting up a sequencing pipeline or benchmarking the performance of different algorithms limits the implementation and uptake of cancer genomics. Here, we describe reference call sets obtained from paired tumor-normal genomic DNA (gDNA) samples derived from a breast cancer cell line-which is highly heterogeneous, with an aneuploid genome, and enriched in somatic alterations-and a matched lymphoblastoid cell line. We partially validated both somatic mutations and germline variants in these call sets via whole-exome sequencing (WES) with different sequencing platforms and targeted sequencing with >2,000-fold coverage, spanning 82% of genomic regions with high confidence. Although the gDNA reference samples are not representative of primary cancer cells from a clinical sample, when setting up a sequencing pipeline, they not only minimize potential biases from technologies, assays and informatics but also provide a unique resource for benchmarking 'tumor-only' or 'matched tumor-normal' analyses.
Bioinformatics Research and Early Development Roche Sequencing Solutions Inc Belmont CA USA
Biomarker Development Novartis Institutes for Biomedical Research Basel Switzerland
Center for Biologics Evaluation and Research FDA Silver Spring MD USA
Center for Devices and Radiological Health FDA Silver Spring MD USA
Center for Drug Evaluation and Research FDA Silver Spring MD USA
Center for Genomics Loma Linda University School of Medicine Loma Linda CA USA
Computational Genomics Genomics Research Center AbbVie North Chicago IL USA
Department of Basic Science Loma Linda University School of Medicine Loma Linda CA USA
Department of Biological Sciences Virginia Tech Blacksburg VA USA
Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA
Estonian Genome Centre Institute of Genomics University of Tartu Tartu Estonia
European Infrastructure for Translational Medicine Amsterdam the Netherlands
Genentech a member of the Roche group South San Francisco CA USA
Illumina Inc Foster City CA USA
Immuneering Corporation Boston MA USA
IMTM Faculty of Medicine and Dentistry Palacky University Olomouc Czech Republic
Institute for Molecular Medicine Finland University of Helsinki Helsinki Finland
National Center for Toxicological Research FDA Jefferson AR USA
Perron Institute for Neurological and Translational Science Nedlands Western Australia Australia
Sentieon Inc Mountain View CA USA
References provided by Crossref.org
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