Skip to main content

No project description provided

Project description

CoVigator logo


CoVigator: monitoring SARS-CoV-2 mutations

PyPI version Run unit tests Powered by Dash License Documentation Status

CoVigator dashboard: https://covigator.tron-mainz.de

CoVigator documentation: https://covigator.readthedocs.io/

Human infections with SARS-CoV-2 are spreading globally since the beginning of 2020, necessitating preventive or therapeutic strategies and first steps towards an end to this pandemic were done with the approval of the first mRNA vaccines against SARS-CoV-2. The accumulation of virus samples that have been sequenced in a short time frame is unprecedented (see Figure 1). This is the first pandemic recorded at a molecular level with such level of detail giving us the opportunity to develop new tools for the monitoring of its evolution.

We want to provide an up-to-date interactive view on SARS-CoV-2 mutations to support global efforts in preventing or treating infections. Monitoring the appearance of relevant new mutations is key to enable a fast reaction to new strains and for that purpose we enable the exploration of these mutations and their annotations (see Figure 2). Thus, we envision to help guiding global vaccine design efforts to overcome the threats of this pandemic.

CoVigator is a monitoring system for SARS-CoV-2 which integrates a full variant calling pipeline, a database that stores all relevant information about mutations in SARS-CoV-2 and finally a dashboard to enable visual analytics.

CoVigator sample accumulation

Figure 1: Sample accumulation by country

  • European Nucleotide Archive (ENA) providing raw reads in FASTQ format
  • Global Initiative on Sharing Avian Influenza Data (GISAID) providing assemblies in FASTA format

CoVigator gene S view

Figure 2: Most frequent mutations in the spike protein

CoVigator loads publicly available SARS-CoV-2 DNA sequences from two databases:

There is certain overlap in the samples present in ENA and GISAID as some national initiatives are systematically reporting to both databases. ENA enables a higher resolution into the SARS-CoV-2 mutation details through the individual reads. This allows us to annotate mutations with a Variant Allele Frequency (VAF) and explore intrahost mutations. On the other hand, while we load all of the GISAID database in CoVigator, we only process the Illumina samples from ENA. This means excluding all of the Oxford Nanopore samples and hence having a partial view of all the available data.

The dashboard is implemented in the visualization framework Dash. The computation is distributed through our cluster with a library of similar name Dask. The analysis pipeline is implemented in the Nextflow framework.

The CoVigator project was developed at the Biomarker Development Center at TRON (Translational Oncology at the University Medical Center of the Johannes Gutenberg University gGmbH). The project was kindly supported by Intel´s Pandemic Response Technology Initiative.

How to cite

  • Schrörs, B., Riesgo-Ferreiro, P., Sorn, P., Gudimella, R., Bukur, T., Rösler, T., Löwer, M., & Sahin, U. (2021). Large-scale analysis of SARS-CoV-2 spike-glycoprotein mutants demonstrates the need for continuous screening of virus isolates. PLOS ONE, 16(9), e0249254. 10.1371/journal.pone.0249254

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

covigator-0.7.2.tar.gz (3.0 MB view details)

Uploaded Source

Built Distribution

covigator-0.7.2-py3-none-any.whl (3.1 MB view details)

Uploaded Python 3

File details

Details for the file covigator-0.7.2.tar.gz.

File metadata

  • Download URL: covigator-0.7.2.tar.gz
  • Upload date:
  • Size: 3.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.4

File hashes

Hashes for covigator-0.7.2.tar.gz
Algorithm Hash digest
SHA256 542fc04a52e6523adbe2a47e246882b317e330297afff89a23607f44bf42f5c7
MD5 e9e9faeae1796ce3a894b890350fd3c1
BLAKE2b-256 060383719b3518158dfcf673c542903c2fb62e2848d77896932a684056f2bb02

See more details on using hashes here.

File details

Details for the file covigator-0.7.2-py3-none-any.whl.

File metadata

  • Download URL: covigator-0.7.2-py3-none-any.whl
  • Upload date:
  • Size: 3.1 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.4

File hashes

Hashes for covigator-0.7.2-py3-none-any.whl
Algorithm Hash digest
SHA256 cd8766428928fb68d4efed6d16bc5d522e25246d088d9f05c27a96aaab59b1ee
MD5 8d456ccd0b632a981deae6883a635add
BLAKE2b-256 4763e475a159269dd57c0cd9d6fbc87ca55a157a4c4397de37df0ef6cb94a1d7

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page