Difference between revisions of "Phylogenetics: Syllabus"

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| Wed., Apr. 18  
 
| Wed., Apr. 18  
 
| '''Divergence Time Estimation'''<br/>Penalized likelihood, Bayesian approaches
 
| '''Divergence Time Estimation'''<br/>Penalized likelihood, Bayesian approaches
| Read for Apr. 25
+
| Read chapter and paper for Apr. 25
 
|-
 
|-
 
| Mon., Apr. 23
 
| Mon., Apr. 23

Revision as of 00:45, 16 April 2007

Adiantum.png EEB 349: Phylogenetics
Lectures: MW 11-12:15 (CUE 320)
Lab: M 1-3 (TLS 477)
Lecture Instructor: Paul O. Lewis
Lab Instructor: Maxi Polihronakis

Lecture Topics

The following syllabus is tentative and probably will change without notice numerous times during the semester. Also, the content of linked presentations may change as well (so if you intend to print out lectures before class, do so as late as possible). Changes made after lectures are given will primarily reflect correction of typographical errors. All content linked to this page is copyright © 2007 by Paul O. Lewis.

Day Lecture Lab/Homework
Wed., Jan. 17 Introduction http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
Significance, history, terminology
http://hydrodictyon.eeb.uconn.edu/eebedia/images/e/ea/Pencil.png Tree from splits
Mon., Jan. 22 Tree thinking http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
Rooted/unrooted, ultrametric/free, paralogy/orthology, lineage sorting, "basal" lineages
http://hydrodictyon.eeb.uconn.edu/eebedia/images/0/0d/Flask.png Nexus data files
Wed., Jan. 24 Consensus trees http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png Parsimony http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png

Camin-Sokal, Wagner, Fitch, Dollo, transversion, generalized, step-matrix

http://hydrodictyon.eeb.uconn.edu/eebedia/images/e/ea/Pencil.png Parsimony
Mon., Jan. 29 Polyphyly vs. Paraphyly Revisited http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png Searching http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
Exhaustive, branch-and-bound, star decomposition, stepwise addition, heuristic, genetic algorithms
http://hydrodictyon.eeb.uconn.edu/eebedia/images/0/0d/Flask.png Searching
Wed., Jan. 31 Distances http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
Least squares criterion, minimum evolution criterion, split decomposition, quartet puzzling, DCM, NJ
http://hydrodictyon.eeb.uconn.edu/eebedia/images/e/ea/Pencil.png Distances
Mon., Feb. 5 Substitution models http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
Transition probability, instantaneous rates, JC69 model, K2P model, F81 model, F84 model, HKY85 model, GTR model
http://hydrodictyon.eeb.uconn.edu/eebedia/images/0/0d/Flask.png Distance methods
Wed., Feb. 7 Maximum likelihood http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
Likelihood of a DNA sequence, likelihood of a pair of sequences, parameter estimation (MLEs), likelihood of a tree, likelihood ratio test, simulation
http://hydrodictyon.eeb.uconn.edu/eebedia/images/e/ea/Pencil.png Likelihood
Mon., Feb. 12 Rate heterogeneity http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png Addendum http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png
Proportion of invariable sites, discrete gamma, site-specific rates
http://hydrodictyon.eeb.uconn.edu/eebedia/images/0/0d/Flask.png Likelihood
Wed., Feb. 14 *** Snow day: no class today *** (but do begin working on homework 5) http://hydrodictyon.eeb.uconn.edu/eebedia/images/e/ea/Pencil.png Rate Het.
Mon., Feb. 19 Secondary structure (stem) models http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png Codon models http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
RNA stem/loop structure, compensatory substitutions, stem models, nonsynonymous vs. synonymous rates, codon models
http://hydrodictyon.eeb.uconn.edu/eebedia/images/0/0d/Flask.png Using the cluster
Wed., Feb. 21 Bootstrapping http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png Bremer support http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png Topology tests http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
Bootstrapping, Bremer support, KH test, SH test, SOWH test
No homework assignment this week
Mon., Feb. 26 Simulation (updated) http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png Long branch attraction http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png Model selection, part I http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
Stochastic simulation, statistical consistency, long branch attraction, long branch repulsion, likelihood ratio tests, Akaike Information criterion (AIC), Bayesian Information Criterion (BIC)
http://hydrodictyon.eeb.uconn.edu/eebedia/images/0/0d/Flask.png Hy-Phy
Wed., Feb. 28 Data partitioning http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png Expected substitutions (updated) http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
ILD test for combinability, using different model for each partition
http://hydrodictyon.eeb.uconn.edu/eebedia/images/e/ea/Pencil.png Simulation
Mon., Mar. 5 Spring break
no class
no class
Wed., Mar. 7 Spring break no class
Mon., Mar. 12 Bayes primer http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
Conditional/joint probabilities, Bayes rule, prior vs. posterior distributions, probability mass vs. probability density, Markov chain Monte Carlo (start)
http://hydrodictyon.eeb.uconn.edu/eebedia/images/0/0d/Flask.png ModelTest/Gamma dist.
Wed., Mar. 14 Bayesian phylogenetics http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
MCMC (continued), heated chains, choosing prior distributions
http://hydrodictyon.eeb.uconn.edu/eebedia/images/e/ea/Pencil.png MCMC
Mon., Mar. 19 Prior distributions http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
Summarizing posterior distributions, commonly-used prior distributions, problem priors, reversible-jump MCMC, star tree paradox
http://hydrodictyon.eeb.uconn.edu/eebedia/images/0/0d/Flask.png MrBayes
Wed., Mar. 21 Confidence intervals (follow-up on last lecture) http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png  Model Selection, part II http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
Bayes factors, posterior predictive approaches to model selection
http://hydrodictyon.eeb.uconn.edu/eebedia/images/e/ea/Pencil.png LOCAL move
Mon., Mar. 26 Model Selection, part II (4 extra slides) http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/0/0d/Flask.png Mesquite
Wed., Mar. 28 Ancestral Character States http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
Parsimony approach, ML approach, empirical Bayes approach
http://hydrodictyon.eeb.uconn.edu/eebedia/images/e/ea/Pencil.png Anc. states
Mon., Apr. 2 No lecture today No lab today
Wed., Apr. 4 Models for discrete morphological data http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
DNA sequences vs. morphological characters, Symmetric vs. asymmetric 2-state models, Mk model, estimating morphological branch lengths
http://hydrodictyon.eeb.uconn.edu/eebedia/images/e/ea/Pencil.png Mk model
Mon., Apr. 9 Discrete Character Correlation http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png

Continuous Character Correlation http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
Pagel's likelihood ratio test, Felsenstein's threshhold model, Felsenstein's independent contrasts

http://hydrodictyon.eeb.uconn.edu/eebedia/images/0/0d/Flask.png Partitioning/Morphology
Wed., Apr. 11 Stochastic Character Mapping http://hydrodictyon.eeb.uconn.edu/eebedia/images/f/fa/1perpage.png http://hydrodictyon.eeb.uconn.edu/eebedia/images/1/1b/6perpage.png
Concentrated changes test, stochastic mapping for estimating ancestral states and character correlation, SIMMAP demo
http://hydrodictyon.eeb.uconn.edu/eebedia/images/e/ea/Pencil.png Mapping
Mon., Apr. 16 Stochastic Character Mapping (finish) http://hydrodictyon.eeb.uconn.edu/eebedia/images/0/0d/Flask.png BayesTraits
Wed., Apr. 18 Divergence Time Estimation
Penalized likelihood, Bayesian approaches
Read chapter and paper for Apr. 25
Mon., Apr. 23 Inferring key innovations r8s
Wed., Apr. 25 Alignment (guest lecture by Karl Kjer) Reading: Chapter Pdficon small.gif Paper Pdficon small.gif No homework today

Goals of this course

This course is designed to give you the background you need to understand and critically evaluate phylogenetic analyses described in current primary literature, and to design appropriate phylogenetic analyses to address your own research questions.

Unlike many graduate courses, you will not spend a lot of time reading papers in this course. Instead, you will spend time using state-of-the-art software tools and doing homework assignments designed to ensure that you understand the output of the programs.

There is a confusing diversity of programs these days for performing phylogenetic analyses. We will concentrate on only a few so that you will know how to use these well by the end of the course.

Textbook

No textbook is required for this course, although you might find Joe Felsenstein's 2004 book "Inferring Phylogenies" (published by Sinauer) useful.

Labs

The laboratory section of this course is held in the MacCarthy computer lab on the fourth floor of Torrey Life Science (TLS 477). The labs will consist of tutorials that you work through at your own pace

Homeworks

Your grade will be largely based on homework assignments, one of which will be assigned (nearly) every week. These homework assignments should be treated as if they were take-home, open-book exams. You may therefore consult with either me or the TA for the course, but not with fellow students when working on the homeworks.

Projects

In addition to homeworks, you will prepare a term paper to be due the last week of the course. There is a lot of flexibility in the nature of the term paper. If you have data of your own, you may decide to write a paper describing a phylogenetic analysis of these data, using appropriate methods learned during the course. If you are not yet at the stage of your graduate career where you have data of your own, you can do a thorough re-analysis of an existing data set. Finally, it is ok to simply write a review paper describing a particular topic in phylogenetics in depth. If you choose this route, I will encourage you to write a paper suitable for contribution to Wikipedia (this way, your efforts will survive the course and benefit the broader community). Please get my approval of your chosen topic before doing extensive work on your paper.

Links