title: STBase: one million species trees for comparative biology.
abstract: Comprehensively sampled phylogenetic trees provide the most compelling foundations for strong inferences in comparative evolutionary biology. Mismatches are common, however, between the taxa for which comparative data are available and the taxa sampled by published phylogenetic analyses. Moreover, many published phylogenies are gene trees, which cannot always be adapted immediately for species level comparisons because of discordance, gene duplication, and other confounding biological processes. A new database, STBase, lets comparative biologists quickly retrieve species level phylogenetic hypotheses in response to a query list of species names. The database consists of 1 million single- and multi-locus data sets, each with a confidence set of 1000 putative species trees, computed from GenBank sequence data for 413,000 eukaryotic taxa. Two bodies of theoretical work are leveraged to aid in the assembly of multi-locus concatenated data sets for species tree construction. First, multiply labeled gene trees are pruned to conflict-free singly-labeled species-level trees that can be combined between loci. Second, impacts of missing data in multi-locus data sets are ameliorated by assembling only decisive data sets. Data sets overlapping with the user's query are ranked using a scheme that depends on user-provided weights for tree quality and for taxonomic overlap of the tree with the query. Retrieval times are independent of the size of the database, typically a few seconds. Tree quality is assessed by a real-time evaluation of bootstrap support on just the overlapping subtree. Associated sequence alignments, tree files and metadata can be downloaded for subsequent analysis. STBase provides a tool for comparative biologists interested in exploiting the most relevant sequence data available for the taxa of interest. It may also serve as a prototype for future species tree oriented databases and as a resource for assembly of larger species phylogenies from precomputed trees.
authors: School of Plant Sciences, University of Arizona, Tucson, AZ, 85721, United States of America.
authors: Michelle M
authors: MM
authors: McMahon
authors: Department of Computer Science, Iowa State University, Ames, IA, 50011, United States of America.
authors: Akshay
authors: A
authors: Deepak
authors: Department of Computer Science, Iowa State University, Ames, IA, 50011, United States of America.
authors: David
authors: D
authors: Fernández-Baca
authors: Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, United States of America.
authors: Darren
authors: D
authors: Boss
authors: Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, United States of America.
authors: Michael J
authors: MJ
authors: Sanderson
mesh_terms: D001695:Biology / Q000379:methods*; D030541:Databases, Genetic; D014197:Trees / Q000145:classification* / Q000235:genetics*; D014584:User-Computer Interface