Phylogenetics: Syllabus
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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 Long branch attraction Stochastic simulation, statistical consistency, long branch attraction, long branch repulsion |
http://hydrodictyon.eeb.uconn.edu/eebedia/images/0/0d/Flask.png Hy-Phy |
Wed., Feb. 28 | Likelihood ratio tests Data partitioning Molecular clock, branch-specific rate shifts, ILD test for combinability |
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Mon., Mar. 5 | Spring break no class |
no class |
Wed., Mar. 7 | Spring break | no class |
Mon., Mar. 12 | Bayes primer Conditional/joint probabilities, Bayes rule, posterior distribution, probability densities |
Hy-Phy |
Wed., Mar. 14 | Bayesian phylogenetics MCMC, slice sampling, heated chains |
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Mon., Mar. 19 | Bayesian phylogenetics Summarizing posterior distributions, partitioned data |
Phycas |
Wed., Mar. 21 | Bayesian phylogenetics Reversible-jump MCMC, mixture models, star tree paradox |
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Mon., Mar. 26 | Model Selection LRT, AIC, BIC, Bayes factors, posterior predictive approaches |
MrBayes |
Wed., Mar. 28 | Ancestral Character States Parsimony approach, ML approach, empirical Bayes approach |
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Mon., Apr. 2 | Continuous Character Correlation Independent Contrasts |
PAUP* |
Wed., Apr. 4 | Discrete Character Correlation Pagel's likelihood ratio test |
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Mon., Apr. 9 | Stochastic Character Mapping Ancestral states, character correlation, simmap demo |
Mesquite |
Wed., Apr. 11 | Divergence Time Estimation Penalized likelihood, Bayesian approaches |
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Mon., Apr. 16 | To be announced | r8s |
Wed., Apr. 18 | To be announced | |
Mon., Apr. 23 | To be announced | Beast |
Wed., Apr. 25 | To be announced |
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. You are expected to turn in an assignment one week after it is assigned. 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.