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Title: Reliable Confidence Intervals for RelTime Estimates of Evolutionary Divergence Times
Abstract Confidence intervals (CIs) depict the statistical uncertainty surrounding evolutionary divergence time estimates. They capture variance contributed by the finite number of sequences and sites used in the alignment, deviations of evolutionary rates from a strict molecular clock in a phylogeny, and uncertainty associated with clock calibrations. Reliable tests of biological hypotheses demand reliable CIs. However, current non-Bayesian methods may produce unreliable CIs because they do not incorporate rate variation among lineages and interactions among clock calibrations properly. Here, we present a new analytical method to calculate CIs of divergence times estimated using the RelTime method, along with an approach to utilize multiple calibration uncertainty densities in dating analyses. Empirical data analyses showed that the new methods produce CIs that overlap with Bayesian highest posterior density intervals. In the analysis of computer-simulated data, we found that RelTime CIs show excellent average coverage probabilities, that is, the actual time is contained within the CIs with a 94% probability. These developments will encourage broader use of computationally efficient RelTime approaches in molecular dating analyses and biological hypothesis testing.  more » « less
Award ID(s):
1661218
PAR ID:
10294060
Author(s) / Creator(s):
; ; ;
Editor(s):
Su, Bing
Date Published:
Journal Name:
Molecular Biology and Evolution
Volume:
37
Issue:
1
ISSN:
0737-4038
Page Range / eLocation ID:
280 to 290
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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