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Publications [#69199] of Mark Huber

Papers Published

  1. D. Hearn and M. Huber, The Ancestral Distance test: A topdown approach to detect correlated evolution in large lineages with missing character data and incomplete phylogenies, Systematic Biology, vol. 55 no. 5 (October, 2006), pp. 803--817, Taylor & Francis
    (last updated on 2007/08/05)

    We present the ancestral distance test, a new test to detect correlated evolution between two binary traits. It is appropriate for use with phylogenies that lack resolved subclades, branch lengths, and/or comparative data. We define the ancestral distance as the time separating a randomly sampled taxon from its most recent common ancestor (MRCA) that has one or more descendants possessing an independent trait. The sampled taxon either has (target sample) or lacks (non-target sample) a dependent trait. Modeled as a Markov process, we show that the distribution of ancestral distances for the target sample is identical to the non-target sample when characters are uncorrelated, whereas ancestral distances are smaller on average for the target sample when characters are correlated. Simulations suggest that the ancestral distance can be estimated using the time, total branch length, taxonomic rank, or number of speciation events between a sampled taxon and the MRCA. These results are shown to be robust to deviations from Markov assumptions. We also provide a Monte Carlo technique to estimate p-values when full resolved phylogenies with branch lengths are available. Software is available from Hearn. We apply this Monte Carlo approach to a published data set.
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