Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing

标杆管理 计算生物学 基因组学 生物 基因组 DNA测序 全基因组测序 生殖系 遗传学 外显子组测序 突变 DNA 基因 业务 营销
作者
Li Tai Fang,Bin Zhu,Yongmei Zhao,Wanqiu Chen,Zhaowei Yang,Liz Kerrigan,Kurt J. Langenbach,Maryellen de Mars,Charles Lu,Kenneth B. Idler,Howard J. Jacob,Yuanting Zheng,Luyao Ren,Ying Yu,Erich Jaeger,Gary P. Schroth,Ogan D. Abaan,Keyur Talsania,Justin Lack,Tsai-Wei Shen,Zhong Chen,Seta Stanbouly,Bao Tran,Jyoti Shetty,Yuliya Kriga,Daoud Meerzaman,Cu Nguyen,Virginie Petitjean,Marc Sultan,Margaret C. Cam,Monika Mehta,Tiffany Hung,Eric Peters,Rasika Kalamegham,Sayed Mohammad Ebrahim Sahraeian,Marghoob Mohiyuddin,Yunfei Guo,Lijing Yao,Lei Song,Hugo Y. K. Lam,Jir̆ı́ Drábek,Petr Vojta,Roberta Maestro,Daniela Gasparotto,Sulev Köks,Ene Reimann,Andreas Scherer,Jessica Nordlund,Ulrika Liljedahl,Roderick V. Jensen,Mehdi Pirooznia,Zhipan Li,Chunlin Xiao,Stephen T. Sherry,Rebecca Kusko,Malcolm Moos,Eric Donaldson,Živana Težak,Baitang Ning,Weida Tong,Jing Li,Penelope Duerken-Hughes,Claudia Catalanotti,Shamoni Maheshwari,Joe Shuga,Winnie S. Liang,Jonathan J. Keats,Jonathan Adkins,Erica E. Tassone,Victoria Zismann,Timothy K. McDaniel,Jeffrey M. Trent,Jonathan Foox,Daniel Butler,Christopher E. Mason,Huixiao Hong,Leming Shi,Charles Wang,Wenming Xiao,Ogan D. Abaan,Meredith Ashby,Ozan Aygün,Xiaopeng Bian,Thomas M. Blomquist,Pierre R. Bushel,Margaret C. Cam,Fabien Campagne,Qing‐Rong Chen,Tao Chen,Xin Chen,Yunching Chen,Han‐Yu Chuang,Maryellen de Mars,Youping Deng,Eric Donaldson,Jir̆ı́ Drábek,Ben Ernest,Jonathan Foox,Donald Freed,Paul G. Giresi,Ping Gong,Ana Granat,Meijian Guan,Yan Guo,Christos Hatzis,Susan Hester,Jennifer Hipp,Huixiao Hong,Tiffany Hung,Kenneth B. Idler,Howard J. Jacob,Erich Jaeger,Parthav Jailwala,Roderick V. Jensen,Wendell Jones,Rasika Kalamegham,Bindu Kanakamedala,Jonathan J. Keats,Liz Kerrigan,Sulev Köks,Yuliya Kriga,Rebecca Kusko,Samir Lababidi,Kurt J. Langenbach,Eunice Lee,Jian‐Liang Li,Youyong Li,Zhipan Li,Sharon X. Liang,Xue‐Lu Liu,Charles Lu,Roberta Maestro,Christopher E. Mason,Tim McDaniel,Tim R. Mercer,Daoud Meerzaman,Urvashi Mehra,Corey J. Miles,Chris Miller,Malcolm Moos,Ali Moshrefi,Aparna Natarajan,Baitang Ning,Jessica Nordlund,Cu Nguyen,Jai P. Pandey,Brian N. Papas,Anand Pathak,Eric Peters,Virginie Petitjean,Mehdi Pirooznia,Maurizio Polano,Arati Raziuddin,Wolfgang Resch,Luyao Ren,Andreas Scherer,Gary P. Schroth,Fayaz Seifuddin,Stephen T. Sherry,Jyoti Shetty,Leming Shi,Tieliu Shi,Louis M. Staudt,Marc Sultan,Živana Težak,Weida Tong,Bao Tran,J.M. Trent,Tiffany Truong,Petr Vojta,Cristobal Juan Vera,Ashley Walton,Charles Wang,Jing Wang,Jingya Wang,Mingyi Wang,James C. Willey,Weida Tong,Chunlin Xiao,Wenming Xiao,Xiaojian Xu,Chunhua Yan,Gökhan Yavaş,Ying Yu,Chaoyang Zhang,Yuanting Zheng
出处
期刊:Nature Biotechnology [Springer Nature]
卷期号:39 (9): 1151-1160 被引量:59
标识
DOI:10.1038/s41587-021-00993-6
摘要

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. Tumor–normal paired DNA samples from a breast cancer cell line and a matched lymphoblastoid cell line enable calibration of clinical sequencing pipelines and benchmarking ‘tumor-only’ or ‘matched tumor–normal’ analyses.
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