Multivariate MAPIT analysis of binding affinities in broadly neutralizing antibodies.

This data set contains the return object from the multivariate MAPIT method, applied to two binding affinity traits for two broadly neutralizing antibodies. It also contains the regression coefficients on the same data as reported by Phillips et al. (2021).

phillips_data

Format

A named list containing tibble data frames:

fisher

Tibble containing among other columns the residue id, p-values, antibody species, trait of the Phillips data. Combined p-value with Fisher's method.

harmonic

Tibble containing among other columns the residue id, p-values, antibody species, trait of the Phillips data. Combined p-value with harmonic mean p method.

regression

Named list containing two tibbles containing regression coefficients as reported by Phillips et al.

Source

vignette/study-phillips-bnabs.Rmd

Details

The antibody CR9114 was analyzed with influenza H1 and H3. The antibody CR6261 was analyzed with influenza H1 and H9.

In the data, the p-values are computed for the test whether a given residue position has a marginal epistatic effect on the binding affinities.

Phillips et al. (2021) Binding affinity landscapes constrain the evolution of broadly neutralizing anti-influenza antibodies. eLife 10:e71393