Quantitative Phylogenetics

Spring 2014

Powerpoints from Lectures:

Week 1


Introduction (JBW)

Lecture 1

Wed. Jan 18

Introduction to Phylogenetics
Reading: Goldman and Yang 2008

Fri Jan 20

Lab: Data file formats, tree file formats, data editing and file conversion tools

Week 2

Homology (JBW)

 Lecture 2

Mon. Jan 23

Homology and sequence alignment


Wed. Jan 25

Approaches to sequence alignment

 Assignment 1

Friday, Jan 27

Lab: BLAST, sequence alignment

Week 3

Parsimony Analysis (JBW)

Lecture 3

Mon. Jan. 30

Basic parsimony analysis.

Lecture 4

Wed. Feb 1

Character optimization and models of character state change

Assignment 2

Fri. Feb. 3

Lab: Parsimony analysis, character optimization

Week 4

Advanced Parsimony Analysis (JBW)

 Lecture 5

Mon Feb 6

Strategies and algorithms for heuristic parsimony analysis
Reading: Goloboff 1999
One-page proposal for Final project due.

Lecture 6

Wed Feb 8

Resampling methods, Bremer Support

Assignment 3

Fri Feb 10

Lab: Advanced parsimony analysis

Week 5


Distance-Based Methods (JBW)

Lecture 7

Mon Feb 13

Measures of molecular distance.
reading from text: 4. Genetic distances and nucleotide substitution models

Lecture 8

Wed Feb 15

Clustering algorithm.
reading from text: 5. Phylogenetic inference based on distance methods

Fri Feb 17

Lab: Phenetic analysis of molecular data, MEGA/PAUP*

Week 6


Model-Based Methods: Maximum Likelihood Methods (MM)

Lecture 9

Mon Feb 20

Substitution rate matrices, nucleotide frequencies, other model parameters.

Lecture 10

Wed Feb 22

Model Selection

Fri Feb 24

Lab: JModelTest
Draft Alignment for final project due

Week 7

Model-Based Methods: Maximum Likelihood Methods continued (MM)
reading from text: 6 Phylogenetic inference using maximum likelihood methods

 Lecture 11

Mon Feb. 27

Implementing a Maximum Likelihood analysis


Wed Feb 29

Different algorithms and ML programs


Fri Mar 2

Lab:  Implementing a Maximum Likelihood analysis (Paup, PhyML, RAxML and GARLI)

Week 8


Model-Based Methods: Bayesian Analysis (MM)
reading from text:
7 Bayesian phylogenetic analysis using MRBAYES

Lecture 12

Mon Mar 5

Bayesian inference methods in phylogenetics.

Lecture 12b

Wed Mar 7

Bayesian methods, continued

Fri Mar 9

Lab: Implementing a Bayesian analysis; MrBayes.

Mar 12-16


Spring Break (NO CLASSES)

Week 9

Data Partitions (MM)

Lecture 13

Mon Mar 19

Strategies for analysis of heterogeneous data sets. Partitioned Bremer Support, tests for data congruence.
Readings: Lambkin 2004, Li et al. 2008.


Wed Mar 21

Class discussion.

Fri Mar 23

Ecological Integration Symposium (no lab)

Week 10   Gene Trees vs. Species Trees (MM)
Lecture 14 Mon Mar 26 Gene trees vs. species trees, deep coalescence and lineage sorting, the "anomaly zone"
  Wed Mar 28 Analytical approaches to gene tree discordance
  Fri Mar 30 Lab: Species tree analyses (BEST, *Beast, BUCKy)

Week 11


Testing Hypotheses: comparative analyses (JBW)

Lecture 15

Mon Apr 2

Use of phylogenetic frameworks for hypothesis testing, Independent Contrasts.
Reading: Garland et al. 2005


Wed Apr 4

Class Discussion.

Fri Apr 6

Reading day: no classes

Week 12

Testing Hypotheses: Topology Comparisons and Molecular Clock (MM)

Lecture 16

Mon Apr 9

Topology Comparisons:  AU test and SOWH test

Lecture 17

Wed Apr 11

Parametric bootstrap

Fri Apr 13

Lab: Topology comparisons

Week 13   Rate Heterogeneity and the Molecular Clock (MM)
  Mon. Apr 16 Tests of molecular clock
  Wed Apr 18 Analytical approaches
  Fri Apr 20 Lab: Identifying rate heterogeneity among lineages, BEAST and Multidivtime
Week 14   Open: unfinished topics or suggestions for additional topics (MM)
  Mon Apr 23 To be determined.
  Wed. Apr 25 To be determined.
  Fri Apr 27 Open Lab: we will be in the laboratory to help you with any final issues with the analyses for your projects, presentation of results, etc.

Week 15


Mon Apr 30

Prep Day, classes meet: Course Evaluations.  Open discussion, critique of course, suggestions, problems encountered during course, etc.


Tues May 1

Redefined as Friday. No lab scheduled. Lab will be open for help in completing final project reports.

Wed May 2

Reading day; No class.

Fri May 4

Reading day; No class.  Final Paper due.