Introduction

nfcore/viralrecon is a bioinformatics analysis pipeline used to perform assembly and intrahost/low-frequency variant calling for viral samples. The pipeline currently supports metagenomics and amplicon sequencing data derived from the Illumina sequencing platform.

This pipeline is a re-implementation of the SARS_Cov2_consensus-nf and SARS_Cov2_assembly-nf pipelines initially developed by Sarai Varona and Sara Monzon from BU-ISCIII. Porting both of these pipelines to nf-core is an international collaboration between numerous contributors and developers. We appreciated the need to have a portable, reproducible and scalable pipeline for the analysis of COVID-19 sequencing samples and so the Avengers Assembled! Please come and join us and add yourself to the contributor list :)

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with docker containers making installation trivial and results highly reproducible.

We have integrated a number of options in the pipeline to allow you to run specific aspects of the workflow if you so wish. For example, you can skip all of the assembly steps with the --skip_assembly parameter. See usage docs for all of the available options when running the pipeline.

Pipeline summary

1. Download samples via SRA, ENA or GEO ids (ENA FTP, parallel-fastq-dump; if required)
2. Raw read QC (FastQC)
3. Adapter trimming (fastp)
4. Merge re-sequenced FastQ files (cat)
5. Variant calling
   1. Read alignment (Bowtie 2)
   2. Sort and index alignments (SAMtools)
   3. Primer sequence removal (iVar; amplicon data only)
   4. Alignment-level QC (SAMtools, picard)
   5. Choice of multiple variant calling routes
      • Call variants (VarScan 2)
        • Consensus sequence generation (BCFTools, BEDTools)
        • Variant annotation (SnpEff, SnpSift)
        • Consensus assessment report (QUAST)
      • Call variants (iVar)
        • Consensus sequence generation (iVar)
        • Variant annotation (SnpEff, SnpSift)
        • Consensus assessment report (QUAST)
6. De novo assembly
   1. Primer trimming (Cutadapt; amplicon data only)
   2. Removal of host reads (Kraken 2)
   3. Choice of multiple assembly tools (SPAdes, metaSPAdes, Unicycler, minia)
      • Blast to reference genome (blastn)
      • Contiguate assembly (ABACAS)
      • Assembly report (PlasmidID)
      • Assembly assessment report (QUAST)
      • Call variants relative to reference (Minimap2, seqwish, vg)
      • Variant annotation (SnpEff, SnpSift)
7. Present QC and visualisation for raw read, alignment, assembly and variant calling results (MultiQC, Bandage)

Quick Start

i. Install nextflow

ii. Install either Docker or Singularity for full pipeline reproducibility (please only use Conda as a last resort; see docs)

iii. Download the pipeline and test it on a minimal dataset with a single command

nextflow run nf-core/viralrecon -profile test,<docker/singularity/conda/institute>

Please check nf-core/configs to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use -profile <institute> in your command. This will enable either docker or singularity and set the appropriate execution settings for your local compute environment.

iv. Start running your own analysis!

nextflow run nf-core/viralrecon -profile <docker/singularity/conda/institute> --input samplesheet.csv --genome 'NC_045512.2' -profile docker

See usage docs for all of the available options when running the pipeline.

Documentation

The nf-core/viralrecon pipeline comes with documentation about the pipeline, found in the docs/ directory:

1. Installation
2. Pipeline configuration
   • Local installation
   • Adding your own system config
   • Reference genomes
3. Running the pipeline
4. Output and how to interpret the results
5. Troubleshooting

Credits

nf-core/viralrecon was originally written by Sarai Varona, Miguel Juliá and Sara Monzon from BU-ISCIII and co-ordinated by Isabel Cuesta for the Institute of Health Carlos III, Spain. Through collaboration with the nf-core community the pipeline has now been updated substantially to include additional processing steps and to standardise inputs/outputs.

Many thanks to others who have helped out and contributed along the way too, including (but not limited to):

Name	Affiliation
Alexander Peltzer	Boehringer Ingelheim, Germany
Alison Meynert	University of Edinburgh, Scotland
Edgar Garriga Nogales	Centre for Genomic Regulation, Spain
Erik Garrison	UCSC, USA
Gisela Gabernet	QBiC, University of Tübingen, Germany
Harshil Patel	The Francis Crick Institute, UK
Joao Curado	Flomics Biotech, Spain
Jose Espinosa-Carrasco	Centre for Genomic Regulation, Spain
Katrin Sameith	DRESDEN-concept Genome Center, Germany
Marta Pozuelo	Flomics Biotech, Spain
Maxime Garcia	SciLifeLab, Sweden
Michael Heuer	UC Berkeley, USA
Phil Ewels	SciLifeLab, Sweden
Simon Heumos	QBiC, University of Tübingen, Germany
Stephen Kelly	Memorial Sloan Kettering Cancer Center, USA
Thanh Le Viet	Quadram Institute, UK

Listed in alphabetical order

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

For further information or help, don't hesitate to get in touch on Slack (you can join with this invite).

Citation

You can cite the nf-core publication as follows:

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x. ReadCube: Full Access Link

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.