Detect interesting SARS-CoV-2 spike protein variants from Sanger sequencing data.
Detect interesting SARS-CoV-2 spike protein mutations from Sanger sequencing data
covid-spike-classification is a script to call interesting SARS-CoV-2 spike protein mutations
from Sanger sequencing to support the Danish COVID-19 monitoring efforts.
Using Sanger-sequenced RT-PCR product of the spike protein, this tool should pick up all relevant
mutations currently tracked (see
for the full list of tracked mutations) and give a table with one row per sample and a
yes/no/failed column per tracked mutation.
This workflow is built and maintained at https://github.com/kblin/covid-spike-classification
If you found this tool useful, please cite https://www.medrxiv.org/content/10.1101/2021.03.27.21252266v1
covid-spike-classification is distributed via this git repository, pypi or bioconda.
Installing via bioconda is the fastest way to get up and running:
conda create -n csc -c conda-forge -c bioconda covid-spike-classification conda activate csc
git & pypi
When installing via git or pypi, you first need to install the external binary dependencies.
covid-spike-classification depends on three excellent tools to do most of the work:
- tracy (versions 0.5.3 & 0.5.7 tested)
- bowtie2 (version 2.4.2 tested)
- samtools (versions 1.10 & 1.11 tested)
If you have
conda installed, the easiest way to get started is to just install these via calling
git clone https://github.com/kblin/covid-spike-classification.git cd covid-spike-classification conda env create -n csc -f environment.yml conda activate csc pip install .
Docker, Podman, Singularity
While not technically an installation method,
covid-spike-classification is also shipped as an OCI container.
To use it, you ideally run the container from a workflow management system like Snakemake
or Nextflow that will take care of mounting filesystems into the container for you.
The OCI container image is available from the Docker Hub
You also need to generate the samtools and bowtie2 indices for your reference genome. We ship a copy of NC_045512 and a script to generate these indices:
conda activate csc cd ref ./build_indices.sh cd ..
Assuming you used above instructions to install via conda, you can run the tool like this:
conda activate csc covid-spike-classification --reference /path/to/your/reference.fasta --outdir /path/to/result/dir /path/to/sanger/reads/dir_or.zip
Notably, you can provide the input either as a ZIP file or as a directory, as long as they directly contain the ab1 files you want to run the analysis on.
See also the
--help output for more detailed usage information.
All code is available under the Apache License version 2, see the
LICENSE file for details.
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