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

Fang LT, Zhu B, Zhao Y, Chen W, Yang Z, Kerrigan L, Langenbach K, de Mars M, Lu C, Idler K, Jacob H, Zheng Y, Ren L, Yu Y, Jaeger E, Schroth GP, Abaan OD, Talsania K, Lack J, Shen TW, Chen Z, Stanbouly S, Tran B, Shetty J, Kriga Y, Meerzaman D, Nguyen C, Petitjean V, Sultan M, Cam M, Mehta M, Hung T, Peters E, Kalamegham R, Sahraeian SME, Mohiyuddin M, Guo Y, Yao L, Song L, Lam HYK, Drabek J, Vojta P, Maestro R, Gasparotto D, Kõks S, Reimann E, Scherer A, Nordlund J, Liljedahl U, Jensen RV, Pirooznia M, Li Z, Xiao C, Sherry ST, Kusko R, Moos M, Donaldson E, Tezak Z, Ning B, Tong W, Li J, Duerken-Hughes P, Catalanotti C, Maheshwari S, Shuga J, Liang WS, Keats J, Adkins J, Tassone E, Zismann V, McDaniel T, Trent J, Foox J, Butler D, Mason CE, Hong H, Shi L, Wang C, Xiao W, Somatic Mutation Working Group of Sequencing Quality Control Phase II Consortium

Nat. Biotechnol. 39 (9) 1151-1160 [2021-09-00; online 2021-09-09]

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.

NGI Uppsala (SNP&SEQ Technology Platform) [Collaborative]

National Genomics Infrastructure [Collaborative]

PubMed 34504347

DOI 10.1038/s41587-021-00993-6

Crossref 10.1038/s41587-021-00993-6

pii: 10.1038/s41587-021-00993-6
pmc: PMC8532138
mid: NIHMS1740806


Publications 7.1.2