Course Description and Objectives

This course provides the advanced student with the specialized aspects of reconstructing phylogenies. The course emphasizes complex modeling and analyses for use in reconstructing evolutionary phylogenies. Students familiar with phylogenetic software (PAUP* and MacClade), DNA sequence analysis software (Sequencher and Clustal W), and WWW resources (GenBank, EMBL, and NCBI) will be expected to integrate their own research or novel datasets into the course. The goal is to provide students with the most advanced tools and technology available to address questions in their own research. This course builds on the introduction to methods provided in BIO5466 or its equivalents at other institutions.

Prerequisites: BIO4369, BIO5466, BIO2450, or by instructor permission
 

Level

Graduate
 

Credit

4 hours:   2 hour lectures and a 3 hour laboratory

*Anyone requiring special assistance with disabilities, religious holidays, or university approved events please contact me immediately in order that any necessary accommodations may be made.

Please note that academic dishonesty is a serious offense and harsh penalties results. Please review the Academic Honesty policy which applies to all Texas State University students.

Class Syllabus

 Week 1

Introduction to the course and lab

 Week 2

Dataset and character assessment

     Lab: Sequencher 4.0 application

 Week 3

Character evolution
     Lab: PAUP 4.0* dataset evaluation

 Week 4

Probability
     Lab: Maximum likelihood in the JC model

 Week 5

Model complexity and computation efficiency
     Lab: ModelTest software

 Week 6

Maximum likelihood model building
     Lab: PAUP 4.0* parameter estimation

 Week 7

Assessing support
     Lab: PAUP 4.0* Quartet puzzling, bootstraps

 Week 8

Analytical conflicts
     Lab: PAUP 4.0* Topology dependent comparisons

 Week 9

Combined analyses
     Lab: Likelihood constraints with morphological characters

 Week 10

Special cases of the maximum likelihood model: unequal rates
     Lab: Long branch attraction

 Week 11

Special cases of the maximum likelihood model: missing data
     Lab: incomplete datafiles

 Week 12

Special cases of the maximum likelihood model: testing hypotheses
     Lab: constrained searches in maximum likelihood

 Week 13

Interpretation of Topologies
     Lab: Assignation of branch length dependent testing and probabilities

 Week 14

Novel methods in maximum likelihood
     Lab: New approaches and other software (Puzzle, Phylip 3.0)