This repository contains all the data used and produced for Halfmann and Minor et al. 2022, Evolution of a globally unique SARS-CoV-2 Spike E484T monoclonal antibody escape mutation in a persistently infected, immunocompromised individual.

You can read the preprint on medRxiv at: https://www.medrxiv.org/content/10.1101/2022.04.11.22272784v2

To reproduce our results, we recommend you clone the project's GitHub repository at https://github.com/dholab/E484T-visualizations/tree/main. You may also reproduce our iSNV analysis, available at https://github.com/dholab/prolonged-infection-suppfig1, and our SARS-CoV-2 Genetic Distance Comparison with our Supplemental Figure 2 workflow, available at https://github.com/dholab/prolonged-infection-suppfig2. All data from the runs used to inform the manuscript and generate figures are available below in the sept2022_revision_VirusEvolution folder. These include all outputs from the nf-core/viralrecon pipeline, which we used to detect low-frequency within-host nucleotide variants. We acknowledge the hard work of the viralrecon developers, as well as the developers behind all the tools in viralrecon, all of whom are cited on GitHub here.

In a previous version of this data availability portal, sequences and metadata from the GISAID EpiCov™ database were made publicly available. We hereby apologize to the GISAID Initiative for redistributing sequence data and metadata, and further apologize to all laboratories and organizations who contributed these data to the GISAID repository, as listed in the Acknowledgement of GISAID Data Contributors available at https://doi.org/10.55876/gis8.220802ed.

The older version of our preprint, as of June 2022, is on medRxiv at: https://www.medrxiv.org/content/10.1101/2022.04.11.22272784v1

To reproduce the results from this submission specifically, we recommend you download the files in the june2022_submission folder below and follow the directions in the file README.md. You can also access these files at https://github.com/nrminor/E484T-visualizations/tree/deprecated. Note that we have since made considerable improvements to the reproducibility and rigor of our analyses. As such, we recommend any efforts to reproduce our results be devoted to our September 2022 revisions workflows, all of which are available to the public on GitHub. We will continue to make previous versions of our workflows available here in the spirit of scientific transparency and openness.