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5 results for “Supermatrices”
Data from: Using supermatrices for phylogenetic inquiry: an example using the sedges
In this article, we use supermatrix data-mining methods to reconstruct a large, highly inclusive phylogeny of Cyperaceae from nucleotide data available on GenBank. We explore the properties of these trees and their utility for phylogenetic inference, and show that even the highly incomplete alignments characteristic of supermatrix approaches may yield very good estimates of phylogeny. We present a novel pipeline for filtering sparse alignments to improve their phylogenetic utility by maximizing the partial decisiveness of the matrices themselves through a technique we call "phylogenetic scaffolding," and we present a new method of scoring tip instability (i.e. "rogue taxa") based on the I statistic implemented in the software Mesquite. The modified statistic, which we call IS, is somewhat more straightforward to interpret than similar statistics, and our implementation of it may be applied to large sets of large trees. The largest sedge trees presented here contain more than 1500 tips (about one quarter of all sedge species) and are based on multigene alignments with more than 20 000 sites and more than 90% missing data. These trees match well with previously supported phylogenetic hypotheses, but have lower overall support values and less resolution than more heavily filtered trees. Our best-resolved trees are characterized by stronger support values than any previously published sedge phylogenies, and show some relationships that are incongruous with previous studies. Overall, we show that supermatrix methods offer powerful means of pursuing phylogenetic study and these tools have high potential value for many systematic biologists.
Data from: Using supermatrices for phylogenetic inquiry: an example using the sedges
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Data from: Resolving ambiguity of concatenation in multi-locus sequence data for the construction of phylogenetic supermatrices
The construction of supermatrices from mining of DNA metadata is problematic due to incomplete species identification and incongruence of gene trees that hamper sequence concatenation based on Linnaean binomials. We applied methods from graph theory to minimize ambiguity of concatenation globally over a large data set. An initial step establishes sequence clusters for each locus that broadly correspond to Linnaean species. These clusters frequently are not consistent with binomials and specimen identifiers, which greatly complicates the concatenation of clusters across multiple loci. A multipartite heuristic algorithm is used to match clusters across loci and to generate a global set of concatenates that minimizes conflict of taxonomic names. The procedure was applied to all available data on GenBank for the Coleoptera (beetles) including >10500 taxon labels for >23500 sequences of four loci. The BlastClust algorithm was used in the initial clustering step, resulting in 11241 clusters or divergent singletons. Clusters were first used for name assignment of unidentified sequences resulting in 510 new identifications (13.9% of total unidentified sequences) of which nearly half were by clustering of a specimen at a secondary locus. Concatenation was straightforward only for 12.8% of all binomials represented by a singleton sequence at each locus with an available entry, while the majority of binomials were associated to multi-sequence clusters in at least one locus. Concatenation of clusters is particularly problematic where limits of DNA-based clusters are inconsistent with the Linnaean binomials, either containing more than one binomial or splitting a binomial among multiple clusters. The current data set contained 1518 such clusters (13.5% of total). By applying a scoring scheme for full and partial name matches in pairs of clusters, the maximum weight set of concatenates produced a matrix of minimally 7366 terminals. Varying the match weights for partial matches had little effect on the number of terminals, although if partial matches were disallowed, the number of terminals increased greatly. Trees from the resulting supermatrices generally produced tree topologies in good agreement with the Linnaean taxonomy, with fewer terminals compared to trees generated according to standard species labels. The study illustrates a strategy for assembling the Tree-of-Life from an ever more complex primary database.
Data from: Resolving ambiguity of concatenation in multi-locus sequence data for the construction of phylogenetic supermatrices
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Data from: Terrace aware data structure for phylogenomic inference from supermatrices
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