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dc.contributor.authorDajles, Andres
dc.date.accessioned2017-12-13T23:03:52Z
dc.date.available2017-12-13T23:03:52Z
dc.date.issued2016-05
dc.identifier.urihttp://hdl.handle.net/11122/8041
dc.descriptionMaster's Project (M.S.) University of Alaska Fairbanks, 2016en_US
dc.description.abstractIt is known that the STAR and USTAR algorithms are statistically consistent techniques used to infer species tree topologies from a large set of gene trees. However, if the set of gene trees is small, the accuracy of STAR and USTAR in determining species tree topologies is unknown. Furthermore, it is unknown how introducing roots on the gene trees affects the performance of STAR and USTAR. Therefore, we show that when given a set of gene trees of sizes 1, 3, 6 or 10, the STAR and USTAR algorithms with Neighbor Joining perform relatively well for two different cases: one where the gene trees are rooted at the outgroup and the STAR inferred species tree is also rooted at the outgroup, and the other where the gene trees are not rooted at the outgroup, but the USTAR inferred species tree is rooted at the outgroup. It is known that the STAR and USTAR algorithms are statistically consistent techniques used to infer species tree topologies from a large set of gene trees. However, if the set of gene trees is small, the accuracy of STAR and USTAR in determining species tree topologies is unknown. Furthermore, it is unknown how introducing roots on the gene trees affects the performance of STAR and USTAR. Therefore, we show that when given a set of gene trees of sizes 1, 3, 6 or 10, the STAR and USTAR algorithms with Neighbor Joining perform relatively well for two different cases: one where the gene trees are rooted at the outgroup and the STAR inferred species tree is also rooted at the outgroup, and the other where the gene trees are not rooted at the outgroup, but the USTAR inferred species tree is rooted at the outgroup.en_US
dc.language.isoen_USen_US
dc.subjectTreesen_US
dc.subjectCladistic analysisen_US
dc.subjectGenome mappingen_US
dc.subjectIdentificationen_US
dc.subjectRootsen_US
dc.titleStatistical analysis of species tree inferenceen_US
dc.typeMaster's Projecten_US
dc.type.degreems
dc.identifier.departmentDepartment of Mathematics and Statistics
dc.contributor.chairRhodes, John
dc.contributor.committeeAllman, Elizabeth
dc.contributor.committeeGoddard, Scott
dc.contributor.committeeShort, Margaret
dc.contributor.committeeBarry, Ron
refterms.dateFOA2020-03-05T14:54:40Z


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