Before revision:   In addition, we show that low-eigenvalue correlation modes, discarded by PCA, are important to recover structural information: the corresponding patterns are highly localized, that is, they are concentrated in few sites, which we find to be in close contact on the three-dimensional protein fold . We also explain why these low-eigenvalue modes, in contrast to the standard principal components, are able to efficiently encode compensatory mutations between pairs of residues .
After revision:  In addition, we show that low-eigenvalue correlation modes, discarded by PCA, are important to recover structural information: the corresponding patterns are highly localized, that is, they are concentrated in few sites, which we find to be in close contact on the three-dimensional protein fold .