BATVI: Fast, sensitive and accurate detection of virus integrations

Area of Science:

• Genomics
• Bioinformatics
• Virology

Background:

• Virus integrations in the human genome are linked to various diseases.
• Existing methods for detecting virus integrations using next-generation sequencing data are often slow and lack sensitivity.

Purpose of the Study:

• To introduce BatVI, a novel and efficient method for predicting viral integrations in the human genome.
• To enhance the speed and sensitivity of viral integration site detection.

Main Methods:

• BatVI employs a rapid screening process to identify chimeric reads indicative of viral integrations.
• Sensitive alignment using BLAST is performed on candidate reads, followed by clustering of co-localized reads.
• Assembly of chimeric reads within clusters enables the extraction of high-confidence viral integration sites.

Main Results:

• BatVI demonstrated an order of magnitude increase in speed compared to existing methods like VirusFinder and VirusSeq.
• The method achieved nearly double the true positive predictions with a false positive rate below 1% on simulated and real datasets.
• Novel viral integrations in TERT and MLL4 genes were identified in liver cancer patient datasets, validated by gene expression data.

Conclusions:

• BatVI offers a significant advancement in the prediction of viral integration sites, outperforming current tools in speed and accuracy.
• The uncovered novel integrations in key genes highlight BatVI's potential for discovering disease-associated viral elements.
• BatVI is available for download, facilitating further research in viral integration studies.