⚠️PLEASE NOTE: This tool was called VOCAL (Variant Of Concern ALert and prioritization) before! Some errors in the naming may subsist in the documentation. Feel free to submit an issue.

VirusWarn-SC2

Mutation-Based Early Warning System to Prioritize Concerning SARS-CoV-2 Variants from Sequencing Data

The goal of VirusWarn-SC2 is to detect SARS-CoV-2 emerging variants from collected bases of genomes, before their annotation by phylogenetic analysis. It does so by parsing SARS-CoV-2 genomes and detecting amino acids mutations in the spike proteins that can be associated with a phenotypic change. The phenotypic changes are annotated according to the knowledge accumulated on previous variants. Owing to the limited size of the genome, convergent evolution is expected to take place.

Documentation

VirusWarn-SC2 is part of VirusWarn

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For more information take a look at the VirusWarn-SC2 Documentation

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Check out the Video Tutorial

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Getting Started

⚠️ Note: 🔌 Right now, VirusWarn-SC2 tested on Linux and Mac system only 💻

Quick Installation

To run the pipeline, you need to have Nextflow and either conda, Docker or Singularity.

Click! If you want to install Nextflow directly, you can use the following one-liner.

wget -qO- https://get.nextflow.io | bash

Click! If you want to set up conda to run the pipeline and install all other dependencies through it, you can use the following steps.

Use the following bash commands if you are working on Linux:

wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh

Use the following bash commands if you are working on Mac:

wget https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh
bash Miniconda3-latest-MacOSX-arm64.sh

Then, Nextflow an be installed over conda:

conda create -n nextflow -c bioconda nextflow
conda activate nextflow

Get / Update VirusWarn-SC2

nextflow pull rki-mf1/viruswarn-sc2

Call help

nextflow run rki-mf1/viruswarn-sc2 -r <version> --help

Running VirusWarn-SC2

With a conda, please run:

nextflow run rki-mf1/viruswarn-sc2 -r <version> \
     -profile conda,local \
     --fasta 'test/sample-test.fasta'

With a Docker, please run:

nextflow run rki-mf1/viruswarn-sc2 -r <version> \
     -profile docker,local \
     --fasta 'test/sample-test.fasta'

With a Singularity, please run:

nextflow run rki-mf1/viruswarn-sc2 -r <version> \
     -profile singularity,local \
     --fasta 'test/sample-test.fasta'

With metadata file

nextflow run rki-mf1/viruswarn-sc2 -r <version> \
     -profile conda,local \
     --fasta 'test/sample-test.fasta' \
     --metadata 'test/meta.tsv' \
     --psl

⚠️ Note: Metadata must have the following information at least

• ID column (match with sample ID in FASTA file)
• LINEAGE column (e.g., B.1.1.7, BA.1)

With pblat

🐌 Slow?: The alignment option in VOCAL uses a biopython pairwise aligner and can be relatively slow. It is thus recommended to first generate an alignment file of all the sequences before running VOCAL annotation of the mutations. The alignment file (in PSL format) can be created using the tool pblat by adding the option --psl.

nextflow run rki-mf1/viruswarn-sc2 -r <version> \
     -profile conda,local \
     --fasta 'test/sample-test.fasta' \
     --psl

⚠️ Note: When VirusWarn-SC2 is run without option --psl, it realigns each query sequence to the reference sequence Wuhan NC_045512 using the pairwise alignment function in the biopython library.

With covSonar

You can also build a covSonar database with your sequences. Then you generate a csv file with the match command. The csv file is a valid input for VirusWarn-SC2 and allows to completely skip the alignment step.

nextflow run rki-mf1/viruswarn-sc2 -r <version> \
     -profile conda,local \
     --fasta 'test/covsonar.csv' --year 2021 \
     --covsonar

Parameter list

fasta                    REQUIRED! Path to the input file. Fasta file (or covSonar csv).
                         [ default: '' ]
metadata                 The path to a metadate file for the sequences.
                         [ default: '' ]
year                     Specify the year from which the information should 
                         be used for the ranking.
                         [ default: 2022 ]
psl                      Run process with pblat alignment.
                         [ default: false ]
covsonar                 Input file is not a fasta file but a csv file from covsonar.
                         [ default: false ]
strict                   Run process with strict alert levels (without orange).
                         [ default: 'n' ]

How to interprete result.

VirusWarn-SC2 output an alert level in four different colours which can be classified into 3 ratings.

Alert color	Description	Impact
Pink	Variant is known as VOC/VOI and containing MOC or new mutations.	HIGH
Red	Not VOC/VOI but contain high MOC or ROI, and a new matuation (likely to cause a problem/ new dangerous).	HIGH
Orange	Variant contains moderately muations, or also possibly consider them either VUM or De-escalated variant.	MODERATE
Grey	Near-zero mutation size for MOC or ROI or either no MOC or no ROI.	LOW

Examples for the HTML report can be found in the folder example.

Contact

Did you find a bug? 🐛 Suggestion/Feedback/Feature request? 👨‍💻 Please visit GitHub Issues

For business inquiries or professional support requests 🍺 Please feel free to contact us!

Acknowledgments

• Original Idea: SC2 Evolution Working group
• Funding: Supported by the European Centers for Disease Control [grant number ECDC GRANT/2021/008 ECD.12222].