FW: Penn Bioinformatics Forum -- Wed. November 10th with Dr. Michael Cummings

John T Lonsdale john@johnlonsdale.net
Mon, 01 Nov 2010 11:01:28 PDT
The information below might be of interest:


Penn Bioinformatics Forum


Dr. Michael Cummings

Associate Professor

Center for Bioinformatics and Computational Biology

University of Maryland


Wednesday, November 10, 2010

CRB Austrian Auditorium. --- (directions


(Reception held in the CRB Lobby @ 4:30pm)


Quantifying lineage divergence: the genealogical sorting index


Abstract -


Despite the many speciation mechanisms and the equally diverse range of
species concepts, the divergence of species should be reflected in the
genealogy of most loci. Ultimately gene copies at a given locus within
species should share a common evolutionary history to the exclusion of gene
copies within other species, that is, they will form monophyletic groups.
The standard categorical phylogenetic concepts of polyphyly, paraphyly, and
monophyly describe qualitative relation- ships among organismal groups (such
as species) and fail to quantify the degree of genealogical divergence along
a continuum. To address this problem we introduce a statistic, the
genealogical sorting index (gsi), for quantifying the degree of exclusive
ancestry of labeled groups on a rooted genealogy and demonstrate its
application. The statistic is simple, intuitive, and easily calculated. It
has a normalized range to facilitate comparisons among different groups,
trees, or studies and it provides information on individual groups rather
than a composite measure for all groups. It naturally handles polytomies and
accommodates measures of uncertainty in phylogenetic relationships. We use
coalescent simulations to explore the behavior of the gsi across a range of
divergence times, with the mean value increasing to 1, the maximum value
when exclusivity within a group reached monophyly. Simulations also
demonstrate that the power to reject the null hypothesis of mixed
genealogical ancestry increased markedly as sample size increased, and that
the gsi provides a statistically more powerful measure of divergence than
Fst. Applications to data from published studies demonstrated that the gsi
provides a useful way to detect significant exclusivity even when groups are
not monophyletic. Although we describe this statistic in the context of
divergence, it is more broadly applicable to quantify and assess the
significance of clustering of observations in labeled groups on any tree.




John T Lonsdale PhD
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