HGT-ID

HGT-ID identifies viral integration events in the human genome from whole-genome sequencing (WGS) and RNA-sequencing data to detect horizontal gene transfer relevant to oncology.

Key Features:

• Four-step workflow: Pre-processing of unaligned reads, virus detection using a subtraction approach, identification of integration sites from discordant and soft-clipped reads, and prioritization of HGT candidates by a scoring function.
• Annotation and visualization: Generates detailed annotation and visualization of detected viral integrations.
• Primer design: Designs primers specific to identified integration sites to support experimental validation.
• Sequencing applicability: Operates on next-generation sequencing data including WGS and RNA-sequencing.
• Performance evaluation: Evaluated on cervical cancer samples for human papillomavirus (HPV) integrations and on TCGA WGS liver tumor–normal pairs for hepatitis B virus (HBV) integrations, with cross-validation using RNA-sequencing and a reported absence of HGT in 220 breast tumor WGS samples.

Scientific Applications:

• Viral oncogenesis studies: Detection and characterization of HPV and HBV integration events in cancer genomes such as cervical and liver tumors.
• Horizontal gene transfer research: Identification and prioritization of HGT events in the human genome using sequencing data.
• Cross-platform validation: Integration calling and confirmation across WGS and RNA-sequencing datasets.
• Experimental validation planning: Providing primer designs for PCR-based validation of predicted integration sites.

Methodology:

Computational steps include pre-processing unaligned reads, subtractive virus detection, identification of integration sites via discordant and soft-clipped reads, and prioritization of candidates using a scoring function.