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⚠️Note: 🔌 Right now, VOCAL tested on Linux and Mac system only 💻

clone this repository:

git clone https://github.com/rki-mf1/vocal.git

You can easly install all dependencies with conda:

cd vocal
conda env create -n vocal -f environment.yml
conda activate vocal

... in three steps.

python vocal/vocal.py -i test-data/sample-test.fasta -o results/variant_table.tsv

This creates by default a variant_table.tsv file with all mutations.

⚠️Note: when VOCAL is run without option, it realigns each query sequence to the reference Wuhan sequence NC_045512 using the pairwise alignment function in the biopython library.

🐌 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 that can be downloaded here or simply installed through our provided conda environment.

👀 Thus, if we want to use precomputed whole-genome alignments of the fasta file as a PSL file ( --PSL option) to improve alignment speed please see the below section, otherwise please continue to step2.

To generate a PSL file with alignments

Example command to generate PSL format.

pblat test-data/ref.fna test-data/sample-test.fasta -threads=4 results/output.psl

To run VOCAL with a PSL file;

python vocal/vocal.py -i test-data/sample-test.fasta --PSL results/output.psl -o results/variant_table.tsv

python vocal/Mutations2Function.py -i results/variant_table.tsv -a data/table_cov2_mutations_annotation.tsv -o results/variants_with_phenotypes.tsv 

By default, this step will create the consolidated table ("variants_with_phenotypes.tsv") of mutations with phenotype annotation.

Rscript --vanilla "vocal/Script_VOCAL_unified.R" \
-f results/variants_with_phenotypes.tsv \
-o results/ 

in case we want to include metadata file, use (-a)

Rscript --vanilla "vocal/Script_VOCAL_unified.R" \
-f results/variants_with_phenotypes.tsv \
-a test-data/meta.tsv \
-o results/ 

⚠️Note: meta data must have these information

• ID column (match with sample ID in FASTA file)
• LINEAGE column (e.g., B.1.1.7, BA.1)
• SAMPLING DATE column (the date that a sample was collected) (format YYYY-mm-dd)

Finally, we can easily generate report into HTML format at the end of the analysis.

python  vocal/Reporter.py  \
        -s results/vocal-alerts-samples-all.csv \
        -c results/vocal-alerts-clusters-summaries-all.csv \
        -o results/vocal-report.html 

Please visit Explore the docs »

Vocal output an alert level in 5 different colours which can be classified into 3 ratings.

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

For business inquiries or professional support requests 🍺 please contact Dr. Hölzer, Martin([email protected]) or Dr. Richard, Hugues ([email protected])

• Original Idea: SC2 Evolution Working group at the Robert Koch Institute in Berlin

• Funding: Supported by the European Centers for Disease Control [grant number ECDC GRANT/2021/008 ECD.12222].