ENTOM 4610

Model-Based Phylogenetics and Hypothesis Testing

Course Description

Course information provided by the Courses of Study 2014-2015.

A variety of disciplines in biological research address questions that rely on a phylogenetic framework for hypothesis-testing, including the fields of ecology, epidemiology, behavior, physiology, evolution, and genomics. This course will provide an advanced undergraduate/graduate level introduction to model-based methods of phylogenetic analysis including maximum likelihood and Bayesian methods. The emphasis will be on DNA sequence data and issues associated with reconstructing phylogenetic trees from multiple gene loci. In addition, the course will cover how phylogenies can be used in the context of evolutionary hypothesis testing (including fossil-calibrated phylogenies, character mapping, ancestral state reconstruction, community ecology, and historical biogeography) using rigorous statistical methods. The course will include a computer laboratory for performing analyses using real data sets. Beginning skills in R programming will be introduced, and students will build an independent dataset to analyze using the techniques introduced in class.

When Offered Spring.

Prerequisites/Corequisites Prerequisite: BIOEE 1780 or BIOMG 2800 or equivalent, or permission of instructor.

• 1.1 Be able to describe relationships among gene sequences/ individuals/ species based on a phylogeny. 1.2 Build an aligned sequence data set and infer a phylogeny. 1.3 Assess and discuss issues with evaluating statistical support for relationships.
• 2.1 Learn how to use a variety of programs to analyze data in a phylogenetic framework. 2.2 Understand the difference between gene trees and species trees and, given a gene tree, assess statistical support for selection. 2.3 Implement methods for macroevolutionary analyses, including comparative analyses and ancestral reconstruction.
• Develop alternative hypotheses of evolution and rigorously examine statistical support for these alternatives.
• 4.1 Develop an independent project based on the student's own interests. 4.2 Build a dataset and run appropriate analyses for the individual project. 4.3 Interpret the results of these analyses and communicate findings through scientific writing.
• 5.1 Write questions, hypotheses, and results. 5.2 Discuss scientific literature with peers. 5.3 Present results of independent research.

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