Fast and accurate estimation of the covariance between pairwise maximum likelihood distances
- Published
- Accepted
- Subject Areas
- Computational Biology, Mathematical Biology, Molecular Biology, Computational Science, Statistics
- Keywords
- maximum likelihood, pairwise distance, covariance, correlation, alignment
- Copyright
- © 2014 Gil
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2014. Fast and accurate estimation of the covariance between pairwise maximum likelihood distances. PeerJ PrePrints 2:e387v2 https://doi.org/10.7287/peerj.preprints.387v2
Abstract
Pairwise evolutionary distances are a model-based summary statistic for a set of molecular sequences. They represent the leaf-to-leaf path lengths of the underlying phylogenetic tree. Estimates of pairwise distances with overlapping paths covary because of shared mutation events. It is desirable to take these covariance structure into account in any process that compares or combines distances to increase precision. In this paper, we present a fast estimator for the covariance of two pairwise maximum likelihood distances, estimated under general Markov models. The estimator is based on a conjecture (going back to Nei and Jin, 1989) which links the covariance to path lengths. We prove it here under a simple symmetric substitution model. In a simulation, we show that our estimator outperforms previously published ones in terms of the mean squared error.
Author Comment
This submission is part of the Gaston Gonnet Festschrift.I have changed some formulations, removed typos and added the sentence: "Alternatively, a nonparametric bootstrap can be used (Efron and Tibshirani, 1993), but it takes substantially longer computation times and an requires an MSA too."