Abstract 1658: Performance evaluation of assembly based structural variation discovery in paired tumor normal samples

Abstract Structural variations (SVs) are well known to contribute to genetic diversity of human populations, affect biological functions, and cause various human disorders. However, accurately identifying SVs with correct sizes and locations in the human genome, particularly in cancer samples, remains a challenge due to the complexities of the human genome, limitations of sequencing technologies, and drawbacks of analysis methods. Recent advancement of next-generation sequencing technologies has significantly reduced the sequencing cost, while substantially increased the lengths of the sequencing reads. Therefore, using de novo assembly based approaches for discovering a full spectrum of SVs in human genome becomes tempting. While various assembly methods have been developed and proposed for general use by the community, the relative efficiency and predictive accuracy of SVs calling based on these assembly methods have not been fully evaluated. In this study, we applied several popular de novo assembly tools to the sequencing read data that were generated using multiple sequencing technologies with technical replicates for a paired tumor-normal samples. Assemblies and SVs callsets were generated, and repeatability in the SVs of the technical replicates and reproducibility across sequencing sites were evaluated. Results showed that there were substantial variabilities between SVs callsets based on various assemblies within sequencing platform and cross sequencing sites. We also observed considerable variabilities between assembly based SVs callsets and alignment based SVs callsets. The sources of these variabilities will be further discussed. These results allow better understanding of the impacts of de novo assembly methods on SVs calling, thus providing a better insight to precision medicine. Citation Format: Chunlin Xiao. Performance evaluation of assembly based structural variation discovery in paired tumor normal samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1658.