Fang, Li Tai, Zhu, Bin, Zhao, Yongmei, Chen, Wanqiu, Yang, Zhaowei, Kerrigan, Liz, Langenbach, Kurt, de Mars, Maryellen, Lu, Charles, Idler, Kenneth, Jacob, Howard, Yu, Ying, Ren, Luyao, Zheng, Yuanting, Jaeger, Erich, Schroth, Gary, Abaan, Ogan, Lack, Justin, Shen, Tsai-Wei, Talsania, Keyur, Chen, Zhong, Stanbouly, Seta, Shetty, Jyoti, Kumar, Primal, Bettridge, John, Tran, Bao, Meerzaman, Daoud, Nguyen, Cu, Petitjean, Virginie, Sultan, Marc, Cam, Margaret, Hung, Tiffany, Peters, Eric, Kalamegham, Rasika, Sahraeian, Sayed Mohammad Ebrahim , Mohiyuddin, Marghoob, Yunfei, Guo, Yao, Liking, Song, Lei, Lam, Hugo YK, Drabek, Jiri, Maestro, Roberta, Polano, Maurizio , Kõks, Sulev , Reimann, Ene, Scherer, Andreas, Nordlund, Jessica, Liljedahl, Ulrika, Jensen, Roderick V, Pirooznia, Mehdi, Li, Zhipan, Xiao, Chunlin, Sherry, Steve , Kusko, Rebecca, Moos, Malcolm, Wang, Jing , Donaldson, Eric, Tezak, Zivana, Ning, Baitang, Tong, Weida, Li, Jing, Duerken-Hughes, Penelope, Hong, Huixiao, Shi, Leming, Wang, Charles and Xiao, Wenming (2021) Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing. Nature biotechnology, 39 (9). pp. 1151-1160. ISSN 1546-1696

Abstract

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.

Item Type:	Article
Keywords:	Benchmarking Breast Neoplasms Cell Line, Tumor DNA Mutational Analysis Datasets as Topic Germ Cells High-Throughput Nucleotide Sequencing Humans Mutation Reference Standards Reproducibility of Results Whole Genome Sequencing
Date Deposited:	23 Dec 2021 00:45
Last Modified:	23 Dec 2021 00:45
URI:	https://oak.novartis.com/id/eprint/39647