Abstract
We give an algorithm for discovering co-evolution in biosequences from a dataset consisting of aligned data and a phylogeny. The method correlates vectors of parsimony scores on the edges of a graph, averaged over all optimally parsimonious reconstructions of the data. We describe an efficient data structure, and a preprocessing step that allows for rapid, interactive computation of many correlation scores, at the expense of storage space.
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