Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study

Area of Science:

• Genomics
• Oncology
• Bioinformatics

Background:

• Next-generation sequencing (NGS) is increasingly used in cancer genomics and clinical oncology for personalized medicine.
• Accurate detection of tumor-specific mutations is essential for clinical applications, requiring robust methods and reference data.
• There is a need for standardized practices and datasets to assess the accuracy and reproducibility of NGS-based cancer mutation detection.

Purpose of the Study:

• To establish well-characterized paired tumor-normal reference samples for evaluating NGS-based cancer mutation detection.
• To systematically assess factors influencing the accuracy and reproducibility of somatic mutation detection across various NGS platforms and protocols.
• To generate large-scale whole-genome sequencing (WGS) and whole-exome sequencing (WES) datasets for benchmarking.

Main Methods:

• Generation of paired tumor-normal reference samples.
• Whole-genome sequencing (WGS) and whole-exome sequencing (WES) data generation using 16 library protocols and 7 sequencing platforms across 6 centers.
• Systematic interrogation of somatic mutations within the reference samples.

Main Results:

• Development of a comprehensive dataset from multiple centers, platforms, and protocols using standardized reference samples.
• Identification of key factors impacting the accuracy and reproducibility of somatic mutation detection in cancer genomes.
• Creation of a valuable resource for the validation and benchmarking of NGS technologies and bioinformatics pipelines.

Conclusions:

• The established reference samples and datasets provide a robust platform for evaluating NGS performance in cancer genomics.
• This resource will aid in developing best practices for accurate and reproducible cancer mutation detection.
• The findings support the advancement of NGS applications in clinical oncology and precision medicine.