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Testing adequacy of codon substitution models

dc.contributor.authorTofighi, Fatemeh
dc.contributor.copyright-releaseNot Applicable
dc.contributor.degreeMaster of Science
dc.contributor.departmentDepartment of Mathematics & Statistics - Statistics Division
dc.contributor.ethics-approvalNot Applicable
dc.contributor.external-examinerna
dc.contributor.manuscriptsNot Applicable
dc.contributor.thesis-readerEdward Susko
dc.contributor.thesis-readerJoseph Bielawski
dc.contributor.thesis-supervisorHong Gu
dc.contributor.thesis-supervisorToby Kenney
dc.date.accessioned2024-12-17T15:11:55Z
dc.date.available2024-12-17T15:11:55Z
dc.date.defence2024-12-10
dc.date.issued2024-12-15
dc.description.abstractIn phylogenetic inference, codon substitution models are mainly used to detect positive selection, which is a sign of adaptive molecular evolution at the protein level. Positive selection is identified when non-synonymous substitutions are more frequent than synonymous ones. To model the evolution of amino acid and codon sequences, Markov chains can be used. It's important to test these models for adequacy before drawing phylogenetic conclusions, as inadequate models can lead to unreliable results and incorrect biological interpretations. This thesis introduces several methods to evaluate the adequacy of codon substitution models, such as Pearson's Chisq test with two alternative strategies for binning site patterns; influence matrix based binning and random binning; and the Anderson-Darling test. These methods help determine whether the proposed model effectively fits the data, thereby assessing the reliability of conclusions derived from it.
dc.identifier.urihttps://hdl.handle.net/10222/84809
dc.language.isoen
dc.subjectModel adequacy test
dc.subjectCodon substitution model
dc.subjectPearson’s goodness-of-fit test
dc.titleTesting adequacy of codon substitution models

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