Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing
Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing
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.
- Novartis Institutes for BioMedical Research Switzerland
- Mississippi Institutions of Higher Learning United States
- Weill Cornell Medicine United States
- National Instiutes of Health, National Cancer Institut United States
- Center for Biologics Evaluation and Research United States
Whole Genome Sequencing, DNA Mutational Analysis, Datasets as Topic, High-Throughput Nucleotide Sequencing, Reproducibility of Results, Breast Neoplasms, Reference Standards, Benchmarking, Germ Cells, Cell Line, Tumor, Mutation, Humans
Whole Genome Sequencing, DNA Mutational Analysis, Datasets as Topic, High-Throughput Nucleotide Sequencing, Reproducibility of Results, Breast Neoplasms, Reference Standards, Benchmarking, Germ Cells, Cell Line, Tumor, Mutation, Humans
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