Interactive plot of the distribution of fitness effects of different types of mutations for each viral gene. The dark squares show the median effect of mutations of each type (stop, nonsynonymous, or synonymous), and the light rectangles span the interquartile range. Mutations with negative fitness effects are deleterious.
Note that ORF9b is encoded by an alternative overlapping reading frame with N, which complicates interpretation of selection on mutations in this gene.
You can mouseover the bars for details.
You can click on the mutation type legend to just highlight mutations of a specific type.
The minimum expected count slider below the plot indicates how many expected counts of a mutation we require before making a fitness estimate. Larger values yield more accurate estimates but for fewer mutations. Move the slider to the left to show estimates for more mutations at lower confidence, and move it to the right to show estimates for fewer mutations at higher confidence.
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.
This plot is for the gisaid_2024-04-24 dataset. Here are all plots for that dataset.