Abstract:
BACKGROUND:Many methods for species tree inference require data from a sufficiently large sample of genomic loci in order to produce accurate estimates. However, few studies have attempted to use analytical theory to quantify "sufficiently large". RESULTS:Using the multispecies coalescent model, we report a general analytical upper bound on the number of gene trees n required such that with probability q, each bipartition of a species tree is represented at least once in a set of n random gene trees. This bound employs a formula that is straightforward to compute, depends only on the minimum internal branch length of the species tree and the number of taxa, and applies irrespective of the species tree topology. Using simulations, we investigate numerical properties of the bound as well as its accuracy under the multispecies coalescent. CONCLUSIONS:Our results are helpful for conservatively bounding the number of gene trees required by the ASTRAL inference method, and the approach has potential to be extended to bound other properties of gene tree sets under the model.
journal_name
BMC Bioinformaticsjournal_title
BMC bioinformaticsauthors
Uricchio LH,Warnow T,Rosenberg NAdoi
10.1186/s12859-016-1266-4subject
Has Abstractpub_date
2016-11-11 00:00:00pages
417issue
Suppl 14issn
1471-2105pii
10.1186/s12859-016-1266-4journal_volume
17pub_type
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