Detecting coevolution without phylogenetic trees? Tree-ignorant metrics of coevolution perform as well as tree-aware metrics
Date
2008-12-03
Authors
Caporaso, J Gregory
Smit, Sandra
Easton, Brett
Hunter, Lawrence
Huttley, Gavin Austin
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BioMed Central
Abstract
BACKGROUND: Identifying coevolving positions in protein sequences has myriad applications,
ranging from understanding and predicting the structure of single molecules to generating
proteome-wide predictions of interactions. Algorithms for detecting coevolving positions can be
classified into two categories: tree-aware, which incorporate knowledge of phylogeny, and tree-ignorant,
which do not. Tree-ignorant methods are frequently orders of magnitude faster, but are
widely held to be insufficiently accurate because of a confounding of shared ancestry with
coevolution. We conjectured that by using a null distribution that appropriately controls for the
shared-ancestry signal, tree-ignorant methods would exhibit equivalent statistical power to tree-aware methods. Using a novel t-test transformation of coevolution metrics, we systematically
compared four tree-aware and five tree-ignorant coevolution algorithms, applying them to
myoglobin and myosin. We further considered the influence of sequence recoding using reduced-state
amino acid alphabets, a common tactic employed in coevolutionary analyses to improve both
statistical and computational performance.
RESULTS: Consistent with our conjecture, the transformed tree-ignorant metrics (particularly
Mutual Information) often outperformed the tree-aware metrics. Our examination of the effect of
recoding suggested that charge-based alphabets were generally superior for identifying the
stabilizing interactions in alpha helices. Performance was not always improved by recoding
however, indicating that the choice of alphabet is critical.
CONCLUSION: The results suggest that t-test transformation of tree-ignorant metrics can be
sufficient to control for patterns arising from shared ancestry.
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BMC Evolutionary Biology 8.327 (2008)
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BMC Evolutionary Biology
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Journal article
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