Viral integration detection strategies and a technical update on Virus-Clip
  • DANIEL WAI-HUNG HO1,2,#, XUEYING LYU1,2,#, IRENE OI-LIN NG1,2,*
1 Department of Pathology, The University of Hong Kong, Hong Kong, China
2 State Key Laboratory of Liver Research, The University of Hong Kong, Hong Kong, China
* Address correspondence to: Irene Oi-lin Ng, iolng@hku.hk
# Authors contributed equally to this study
Received 23 April 2021; Accepted 31 May 2021 ; Published online 17 June 2021
Abstract
Oncovirus infection is crucial in human malignancies. Certain oncoviruses can lead to structural variations in the human genome known as viral genomic integration, which can contribute to tumorigenesis. Existing viral integration detection tools differ in their underlying algorithms pinpointing different aspects or features of viral integration phenomenon. We discuss about major procedures in performing viral integration detection. More importantly, we provide a technical update on Virus-Clip to facilitate its usage on the latest human genome builds (hg19 and hg38) and the adoption of multi-thread mode for faster initial read alignment. By comparing the execution of Virus-Clip using single-thread and multi-thread modes of read alignment on targeted-panel sequencing data of HBV-associated hepatocellular carcinoma patients, we demonstrate the marked improvement of multi-thread mode in terms of significantly reduced execution time, while there is negligible difference in memory usage. Taken together, with the current update of Virus-Clip, it will continue supporting the in silico detection of oncoviral integration for better understanding of various human malignancies.
Keywords
Oncovirus, Viral genomic integration, In silico detection, Tumorigenesis, Human malignancies