viroCapt: A Bioinformatics Pipeline for Identifying Viral Insertion in Human Host Genome

Maxime Wack1,2, David Veyer3,4, Camille Peneau5,6

  • 1INSERM, UMRS 1138, Centre de Recherche des Cordeliers. Université de Paris, France.

Abstract

Insights

This study introduces a new bioinformatics pipeline to automatically detect viral insertions in human genomes, crucial for understanding virus-associated cancers. The tool efficiently identifies viral DNA integration sites, aiding cancer research.

Area of Science:

  • Bioinformatics
  • Genomics
  • Oncology

Background:

  • Viruses are implicated in human cancers, with next-generation sequencing enabling deeper investigation.
  • Viral genome integration and oncogene activity are key mechanisms in cancer development.
  • Identifying viral integration sites and oncogenes often requires extensive manual analysis.

Purpose of the Study:

  • To develop an automated analysis and interpretation pipeline for detecting viral insertions in human genomes.
  • To streamline the identification of viral integration sites and oncogenes.
  • To facilitate the study of viral roles in cancer pathophysiology.

Main Methods:

  • Developed a computational pipeline using common bioinformatics tools (bowtie2, samtools, blat).
  • Implemented a dedicated filtering and ranking algorithm in R.
  • Utilized directed viral capture data to identify chimeric reads and putative human sequences.

Main Results:

  • The pipeline successfully infers candidate viral junctions and insertions.
  • Generated static results including tables and figures.
  • Developed an interactive interpretation tool using a Shiny web app.

Conclusions:

  • Validated the pipeline against published data for Human Papillomavirus (HPV), Hepatitis B virus (HBV), and Adeno-associated virus 2 (AAV2) insertions.
  • Demonstrated good information retrieval capabilities for viral insertions.
  • The pipeline offers an efficient method for analyzing viral integration events.

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