# Research Object Crate for ONTViSc (ONT-based Viral Screening for Biosecurity)

Original URL: https://workflowhub.eu/workflows/683/ro_crate?version=3

# ONTViSc (ONT-based Viral Screening for Biosecurity) ## Introduction eresearchqut/ontvisc is a Nextflow-based bioinformatics pipeline designed to help diagnostics of viruses and viroid pathogens for biosecurity. It takes fastq files generated from either amplicon or whole-genome sequencing using Oxford Nanopore Technologies as input. The pipeline can either: 1) perform a direct search on the sequenced reads, 2) generate clusters, 3) assemble the reads to generate longer contigs or 4) directly map reads to a known reference. The reads can optionally be filtered from a plant host before performing downstream analysis. ## Pipeline overview - Data quality check (QC) and preprocessing - Merge fastq files (Fascat, optional) - Raw fastq file QC (Nanoplot) - Trim adaptors (PoreChop ABI - optional) - Filter reads based on length and/or quality (Chopper - optional) - Reformat fastq files so read names are trimmed after the first whitespace (bbmap) - Processed fastq file QC (if PoreChop and/or Chopper is run) (Nanoplot) - Host read filtering - Align reads to host reference provided (Minimap2) - Extract reads that do not align for downstream analysis (seqtk) - QC report - Derive read counts recovered pre and post data processing and post host filtering - Read classification analysis mode - Clustering mode - Read clustering (Rattle) - Convert fastq to fasta format (seqtk) - Cluster scaffolding (Cap3) - Megablast homology search against ncbi or custom database (blast) - Derive top candidate viral hits - Align reads back to top reference and derive coverage statistics (mosdepth and coverM) - De novo assembly mode - De novo assembly (Canu or Flye) - Megablast homology search against ncbi or custom database or reference (blast) - Derive top candidate viral hits - Align reads back to top reference and derive coverage statistics (mosdepth and coverM) - Read classification mode - Option 1 Nucleotide-based taxonomic classification of reads (Kraken2, Braken) - Option 2 Protein-based taxonomic classification of reads (Kaiju, Krona) - Option 3 Convert fastq to fasta format (seqtk) and perform direct homology search using megablast (blast) - Map to reference mode - Align reads to reference fasta file (Minimap2) and derive bam file and alignment statistics (Samtools) Code and detailed instructions can be found [here](https://github.com/eresearchqut/ontvisc). A comprehensive, step-by-step guide on setting up and executing the ONTViSc pipeline across three high-performance computing systems hosted by Australian research and computing facilities - Lyra (Queensland University of Technology), Gadi (National Computational Infrastructure), and Setonix (Pawsey) - utilising the Australian Nextflow Seqera Service, can be found [here](https://mantczakaus.github.io/ontvisc_hpc_seqera_service_guide/). ## Authors Marie-Emilie Gauthier Craig Windell Magdalena Antczak Roberto Barrero

Author
License
  MIT

## Contents

Main Workflow: ONTViSc (ONT-based Viral Screening for Biosecurity)
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Main Workflow Diagram: docs/images/ONTViSc_pipeline.jpeg
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