This repository contains the code for the manuscript "Characterizing SARS-CoV-2 neutralization profiles after bivalent boosting using antigenic cartography" by Annika Rössler, Antonia Netzl, et. al., 2023. Please cite the original publication in Nature Communications if any data or code from this repository is used.
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Raw data can be found in the data directory. The code for the analyses shown in the main manuscript can be found in the code directory. To obtain a titer table for antigenic map construction, execute the excel_to_titertable.R script. To construct maps, first execute the make_map.R followed by the reactivity_adjusted_maps.R scripts. Antibody landscapes are fit in the ablandscapes_fit_multi.R and ablandscapes_fit_idvl.R scripts. The 3D_landscapes.Rmd creates an html script with 3D illustrations of the landscapes.
All SOM analyses can be found in the som directory.
The function directory contains utility functions, including two bash scripts to screenshot and crop html landscapes. For cropping ImageMagick was used:
ImageMagick Studio LLC. (2023). ImageMagick. Retrieved from https://imagemagick.org
All analyses were performed in R version 4.2.2 (2022-10-31). R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
Antigenic maps were constructed using the Racmacs package, Version 1.1.35: Wilks S (2022). Racmacs: R Antigenic Cartography Macros. https://acorg.github.io/Racmacs, https://github.com/acorg/Racmacs.
Antibody landscapes were constructed using the ablandscapes package, Version 1.1.0: Wilks S (2021). ablandscapes: Making Antibody landscapes Using R. R package version 1.1.0, https://github.com/acorg/ablandscapes.
Geometric mean titers and fold changes were calculated using the titertools package, Version 0.0.0.9001: Wilks SH (2022). titertools: A statistical toolkit for the annalysis of censored titration data. R package version 0.0.0.9001.