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

Authors :
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
Source :
Nature biotechnology [Nat Biotechnol] 2021 Sep; Vol. 39 (9), pp. 1151-1160. Date of Electronic Publication: 2021 Sep 09.
Publication Year :
2021

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.<br /> (© 2021. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.)

Details

Language :
English
ISSN :
1546-1696
Volume :
39
Issue :
9
Database :
MEDLINE
Journal :
Nature biotechnology
Publication Type :
Academic Journal
Accession number :
34504347
Full Text :
https://doi.org/10.1038/s41587-021-00993-6