TAILIEUCHUNG - Báo cáo sinh học: "A simulation study comparing supertree and combined analysis methods using SMIDGen"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí y học Molecular Biology cung cấp cho các bạn kiến thức về ngành sinh học đề tài: A simulation study comparing supertree and combined analysis methods using SMIDGen. | Swenson et al. Algorithms for Molecular Biology 2010 5 8 http content 5 1 8 AMR ALGORITHMS FOR MOLECULAR BIOLOGY RESEARCH Open Access A simulation study comparing supertree and combined analysis methods using SMIDGen M Shel Swenson1 Frangois Barbangon2 Tandy Warnow1 C Randal Linder3 Abstract Background Supertree methods comprise one approach to reconstructing large molecular phylogenies given multi-marker datasets trees are estimated on each marker and then combined into a tree the supertree on the entire set of taxa. Supertrees can be constructed using various algorithmic techniques with the most common being matrix representation with parsimony MRP . When the data allow the competing approach is a combined analysis also known as a supermatrix or total evidence approach whereby the different sequence data matrices for each of the different subsets of taxa are concatenated into a single supermatrix and a tree is estimated on that supermatrix. Results In this paper we describe an extensive simulation study we performed comparing two supertree methods MRP and weighted MRP to combined analysis methods on large model trees. A key contribution of this study is our novel simulation methodology Super-Method Input Data Generator or SMIDGen that better reflects biological processes and the practices of systematists than earlier simulations. We show that combined analysis based upon maximum likelihood outperforms MRP and weighted MRP giving especially big improvements when the largest subtree does not contain most of the taxa. Conclusions This study demonstrates that MRP and weighted MRP produce distinctly less accurate trees than combined analyses for a given base method maximum parsimony or maximum likelihood . Since there are situations in which combined analyses are not feasible there is a clear need for better supertree methods. The source tree and combined datasets used in this study can be used to test other supertree and combined analysis methods. .

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