Introduction

This is the Greninger Lab fork of the nf-core/viralrecon pipeline. Visit the official nf-core/viralrecon github and nf-core/viralrecon project for more detailed instructions on how to use this pipeline.

Added/Modified Features

• use --trim_len to specify the minimum read length for fastp to retain
• Mosdepth whole genome coverage graph log10 transformation disabled

Usage

1. Install Nextflow (>=21.10.3)

2. Install Docker

3. Run the pipeline

   • Download the repository locally and modify conf/base.config to ensure computing resource allocation is appropriate for your usage

   • Test it on a minimal dataset:

   nextflow run <VIRALRECON_REPO_DIR/main.nf> -profile test,docker --outdir <OUTDIR>

   • A samplesheet needs to be created to run your own analysis. You can automate samplesheet creation with a bundled python script:

   python <VIRALRECON_REPO_DIR/bin/fastq_dir_to_samplesheet.py> <FASTQ_DIR> viralrecon_samplesheet.csv

   • Example command for Illumina shotgun sequencing QC:

   nextflow run <VIRALRECON_REPO_DIR/main.nf> \
   	--input viralrecon_samplesheet.csv \
   	--outdir <OUTDIR> \
   	--platform illumina \
   	--protocol metagenomic \
   	--fasta <REFERENCE_FASTA> \
   	--trim_len 75 \
   	--skip_markduplicates false \
   	--filter_duplicates true \
   	--skip_nextclade \
   	--skip_pangolin \
   	--skip_assembly \
   	--skip_asciigenome \
   	--skip_consensus \
   	-profile docker

   • Example command for Illumina amplicon sequencing QC:

   nextflow run <VIRALRECON_REPO_DIR/main.nf> \
   	--input viralrecon_samplesheet.csv \
   	--outdir <OUTDIR> \
   	--platform illumina \
   	--protocol amplicon \
   	--fasta <REFERENCE_FASTA> \
   	--primer_bed <AMPLICON_PRIMER_BED_FILE> \
   	--trim_len 75 \
   	--skip_nextclade \
   	--skip_pangolin \
   	--skip_assembly \
   	--skip_asciigenome \
   	--skip_consensus \
   	-profile docker