Nature BiotechnologyBioinformaticsPeer-reviewed journal article
Establishing reference samples for detection of somatic mutations and germline variants with NGS technologies
Li Tai FangiD, Bin ZhuiD, Yongmei ZhaoiD, Wanqiu CheniD, Zhaowei YangiD, Liz Kerrigan, Kurt J. Langenbach, Maryellen de Mars, Charles LuiD, Kenneth B. Idler, Howard J. JacobiD, Yuanting ZhengiD, Luyao ReniD, Ying YuiD, Erich B. JaegeriD, Gary P. SchrothiD, Ogan D. Abaan, Keyur Talsania, Justin LackiD, Tsai-Wei SheniD, Zhong CheniD, Seta StanboulyiD, Bao Quoc TraniD, Jyoti ShettyiD, Yuliya Kriga, , Paul G. Giresi
Abstract
We characterized two reference samples for NGS technologies: a human triple-negative breast cancer cell line and a matched normal cell line. Leveraging several whole-genome sequencing (WGS) platforms, multiple sequencing replicates, and orthogonal mutation detection bioinformatics pipelines, we minimized the potential biases from sequencing technologies, assays, and informatics. Thus, our \"truth sets\" were defined using evidence from 21 repeats of WGS runs with coverages ranging from 50X to 100X (a total of 140 billion reads). These \"truth sets\" present many relevant variants/mutations including 193 COSMIC mutations and 9,016 germline variants from the ClinVar database, nonsense mutations in BRCA1/2 and missense mutations in TP53 and FGFR1. Independent validation in three orthogonal experiments demonstrated a successful stress test of the truth set. We expect these reference materials and \"truth sets\" to facilitate assay development, qualification, validation, and proficiency testing. In addition, our methods can be extended to establish new fully characterized reference samples for the community.
- organism: human
- assay: whole-genome sequencing
- research focus: variant calling
- approach: statistical model
- Citations
- 139
- FWCI
- 9.44
- Field percentile
- top 1%
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