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 covid_spike_classification/core.py
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.
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.
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 ..
Usage
Assuming you used above instructions to install via conda, you can run the tool like this:
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.
License
All code is available under the Apache License version 2, see the
LICENSE file for details.
Detect interesting SARS-CoV-2 spike protein mutations from Sanger sequencing data
covid-spike-classificationis 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
covid_spike_classification/core.pyfor 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
Installation
covid-spike-classificationis distributed via this git repository, pypi or bioconda.Bioconda
Installing via bioconda is the fastest way to get up and running:
git & pypi
When installing via git or pypi, you first need to install the external binary dependencies.
covid-spike-classificationdepends on three excellent tools to do most of the work:If you have
condainstalled, the easiest way to get started is to just install these via callingDocker, Podman, Singularity
While not technically an installation method,
covid-spike-classificationis 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
kblin/covid-spike-classificationrepository.Setup
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:
Usage
Assuming you used above instructions to install via conda, you can run the tool like this:
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
--helpoutput for more detailed usage information.License
All code is available under the Apache License version 2, see the
LICENSEfile for details.