Interactive plots of estimated fitness effects of SARS-CoV-2 amino-acid mutations

Fitness effects estimated from observed versus expected counts of mutations.

Analysis described in Bloom and Neher (2023).

Interactive plots for gisaid_2024-04-24 dataset:

Heatmaps of effects of mutations
Expected counts per site
- neutral mutation rates for each clade
- average per-site counts of each nucleotide mutation type
Distribution of estimated mutation fitness effects
Correlations among effect estimates
Correlations of estimates with deep mutational scanning
Effects of fixed mutations
- fitness effects of mutations fixed in at least one clade
- fitness effects of mutations fixed in a clade versus all mutations
Effects of mutations versus number of descendants
- fitness effects versus number of descendant sequences
Correlations among estimates from different sequence sets
- correlation of fitness effects estimated from different sequence sets
Comparisons to other methods of estimating mutation effects
- correlation of dN/dS with site-average fitness estimates and DMS data
- correlation of mutation effect estimates from other studies with fitness estimates and spike DMS data

See Bloom and Neher (2023) for a paper describing the work.

See https://github.com/jbloomlab/SARS2-mut-fitness for full computer code and data.

See https://jbloomlab.github.io/SARS2-mut-fitness/ for links to all interactive plots.

Here are plots for other datasets: