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Ultra-deep multi-oncopanel sequencing of benchmarking samples with a wide range of variant allele frequencies.

ABSTRACT: The lack of suitable reference genomic material to enable a transparent cross-lab study of oncopanels inspired the SEQC2 Oncopanel Sequencing Working Group to develop four reference samples, sequenced with eight oncopanels at independent test laboratories with ultra-deep sequencing depth. This rich, publicly available dataset enabled performance assessment of the clinical applicability of oncopanels. In addition, this dataset present sample opportunities for developing specific and robust bioinformatics pipelines and fine-tuning parameters for more accurate variant calling, investigating ideal sequencing depth for variant calling of a given minimum VAF and variant type, and also recommending best use cases for Unique Molecular Identifier (UMI) technology.

SUBMITTER: Gong B

PROVIDER: S-EPMC9184574 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Ultra-deep multi-oncopanel sequencing of benchmarking samples with a wide range of variant allele frequencies.

Gong Binsheng B Kusko Rebecca R Jones Wendell W Tong Weida W Xu Joshua J

Scientific data 20220609 1

The lack of suitable reference genomic material to enable a transparent cross-lab study of oncopanels inspired the SEQC2 Oncopanel Sequencing Working Group to develop four reference samples, sequenced with eight oncopanels at independent test laboratories with ultra-deep sequencing depth. This rich, publicly available dataset enabled performance assessment of the clinical applicability of oncopanels. In addition, this dataset present sample opportunities for developing specific and robust bioinf ...[more]

PMID: 35680918

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